Benchmark
Binary classification
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Datasets
Bananas
Bananas dataset.
An artificial dataset where instances belongs to several clusters with a banana shape.
There are two attributes that correspond to the x and y axis, respectively.
Name Bananas
Task Binary classification
Samples 5,300
Features 2
Sparse False
Path /home/kulbach/projects/river/river/datasets/banana.zip
Elec2
Electricity prices in New South Wales.
This is a binary classification task, where the goal is to predict if the price of electricity
will go up or down.
This data was collected from the Australian New South Wales Electricity Market. In this market,
prices are not fixed and are affected by demand and supply of the market. They are set every
five minutes. Electricity transfers to/from the neighboring state of Victoria were done to
alleviate fluctuations.
Name Elec2
Task Binary classification
Samples 45,312
Features 8
Sparse False
Path /home/kulbach/river_data/Elec2/electricity.csv
URL https://maxhalford.github.io/files/datasets/electricity.zip
Size 2.95 MB
Downloaded True
Phishing
Phishing websites.
This dataset contains features from web pages that are classified as phishing or not.
Name Phishing
Task Binary classification
Samples 1,250
Features 9
Sparse False
Path /home/kulbach/projects/river/river/datasets/phishing.csv.gz
SMTP
SMTP dataset from the KDD 1999 cup.
The goal is to predict whether or not an SMTP connection is anomalous or not. The dataset only
contains 2,211 (0.4%) positive labels.
Name SMTP
Task Binary classification
Samples 95,156
Features 3
Sparse False
Path /home/kulbach/river_data/SMTP/smtp.csv
URL https://maxhalford.github.io/files/datasets/smtp.zip
Size 5.23 MB
Downloaded True
Models
Logistic regression
Pipeline (
StandardScaler (
with_std=True
),
LogisticRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.005
)
)
loss=Log (
weight_pos=1.
weight_neg=1.
)
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
)
ALMA
Pipeline (
StandardScaler (
with_std=True
),
ALMAClassifier (
p=2
alpha=0.9
B=1.111111
C=1.414214
)
)
sklearn SGDClassifier
Pipeline (
StandardScaler (
with_std=True
),
SKL2RiverClassifier (
estimator=SGDClassifier(eta0=0.005, learning_rate='constant', loss='log', penalty='none')
classes=[False, True]
)
)
Vowpal Wabbit logistic regression
VW2RiverClassifier ()
Naive Bayes
GaussianNB ()
Hoeffding Tree
HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)
Hoeffding Adaptive Tree
HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=True
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=42
)
Adaptive Random Forest
[]
Streaming Random Patches
SRPClassifier (
model=HoeffdingTreeClassifier (
grace_period=50
max_depth=inf
split_criterion="info_gain"
delta=0.01
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)
n_models=10
subspace_size=0.6
training_method="patches"
lam=6
drift_detector=ADWIN (
delta=1e-05
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
warning_detector=ADWIN (
delta=0.0001
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
disable_detector="off"
disable_weighted_vote=False
seed=None
metric=Accuracy (
cm=ConfusionMatrix (
classes=[]
)
)
)
k-Nearest Neighbors
Pipeline (
StandardScaler (
with_std=True
),
KNNClassifier (
n_neighbors=5
window_size=100
min_distance_keep=0.
weighted=True
cleanup_every=0
distance_func=functools.partial(<function minkowski_distance at 0x7f2d38a59ea0>, p=2)
softmax=False
)
)
ADWIN Bagging
[HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)]
AdaBoost
[HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)]
Bagging
[HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
)]
Leveraging Bagging
[HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)]
Stacking
[Pipeline (
StandardScaler (
with_std=True
),
SoftmaxRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=CrossEntropy (
class_weight={}
)
l2=0
)
), GaussianNB (), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), Pipeline (
StandardScaler (
with_std=True
),
KNNClassifier (
n_neighbors=5
window_size=100
min_distance_keep=0.
weighted=True
cleanup_every=0
distance_func=functools.partial(<function minkowski_distance at 0x7f2d38a59ea0>, p=2)
softmax=False
)
)]
Voting
VotingClassifier (
models=[Pipeline (
StandardScaler (
with_std=True
),
SoftmaxRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=CrossEntropy (
class_weight={}
)
l2=0
)
), GaussianNB (), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), Pipeline (
StandardScaler (
with_std=True
),
KNNClassifier (
n_neighbors=5
window_size=100
min_distance_keep=0.
weighted=True
cleanup_every=0
distance_func=functools.partial(<function minkowski_distance at 0x7f2d38a59ea0>, p=2)
softmax=False
)
)]
use_probabilities=True
)
[baseline] Last Class
NoChangeClassifier ()
Multiclass classification
{
"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
"data": {
"url": "benchmarks/multiclass_classification.csv"
},
"params": [
{
"name": "models",
"select": {
"type": "point",
"fields": [
"model"
]
},
"bind": "legend"
},
{
"name": "Dataset",
"value": "ImageSegments",
"bind": {
"input": "select",
"options": [
"ImageSegments",
"Insects",
"Keystroke"
]
}
},
{
"name": "grid",
"select": "interval",
"bind": "scales"
}
],
"transform": [
{
"filter": {
"field": "dataset",
"equal": {
"expr": "Dataset"
}
}
}
],
"repeat": {
"row": [
"Accuracy",
"MicroF1",
"MacroF1",
"Memory in Mb",
"Time in s"
]
},
"spec": {
"width": "container",
"mark": "line",
"encoding": {
"x": {
"field": "step",
"type": "quantitative",
"axis": {
"titleFontSize": 18,
"labelFontSize": 18,
"title": "Instance"
}
},
"y": {
"field": {
"repeat": "row"
},
"type": "quantitative",
"axis": {
"titleFontSize": 18,
"labelFontSize": 18
}
},
"color": {
"field": "model",
"type": "ordinal",
"scale": {
"scheme": "category20b"
},
"title": "Models",
"legend": {
"titleFontSize": 18,
"labelFontSize": 18,
"labelLimit": 500
}
},
"opacity": {
"condition": {
"param": "models",
"value": 1
},
"value": 0.2
}
}
}
}
Datasets
ImageSegments
Image segments classification.
This dataset contains features that describe image segments into 7 classes: brickface, sky,
foliage, cement, window, path, and grass.
Name ImageSegments
Task Multi-class classification
Samples 2,310
Features 18
Sparse False
Path /home/kulbach/projects/river/river/datasets/segment.csv.zip
Insects
Insects dataset.
This dataset has different variants, which are:
- abrupt_balanced
- abrupt_imbalanced
- gradual_balanced
- gradual_imbalanced
- incremental-abrupt_balanced
- incremental-abrupt_imbalanced
- incremental-reoccurring_balanced
- incremental-reoccurring_imbalanced
- incremental_balanced
- incremental_imbalanced
- out-of-control
The number of samples and the difficulty change from one variant to another. The number of
classes is always the same (6), except for the last variant (24).
Name Insects
Task Multi-class classification
Samples 52,848
Features 33
Classes 6
Sparse False
Path /home/kulbach/river_data/Insects/INSECTS-abrupt_balanced_norm.arff
URL http://sites.labic.icmc.usp.br/vsouza/repository/creme/INSECTS-abrupt_balanced_norm.arff
Size 15.66 MB
Downloaded True
Variant abrupt_balanced
Parameters
----------
variant
Indicates which variant of the dataset to load.
Keystroke
CMU keystroke dataset.
Users are tasked to type in a password. The task is to determine which user is typing in the
password.
The only difference with the original dataset is that the "sessionIndex" and "rep" attributes
have been dropped.
Name Keystroke
Task Multi-class classification
Samples 20,400
Features 31
Sparse False
Path /home/kulbach/river_data/Keystroke/DSL-StrongPasswordData.csv
URL http://www.cs.cmu.edu/~keystroke/DSL-StrongPasswordData.csv
Size 4.45 MB
Downloaded True
Models
Naive Bayes
GaussianNB ()
Hoeffding Tree
HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)
Hoeffding Adaptive Tree
HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=True
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=42
)
Adaptive Random Forest
[]
Streaming Random Patches
SRPClassifier (
model=HoeffdingTreeClassifier (
grace_period=50
max_depth=inf
split_criterion="info_gain"
delta=0.01
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)
n_models=10
subspace_size=0.6
training_method="patches"
lam=6
drift_detector=ADWIN (
delta=1e-05
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
warning_detector=ADWIN (
delta=0.0001
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
disable_detector="off"
disable_weighted_vote=False
seed=None
metric=Accuracy (
cm=ConfusionMatrix (
classes=[]
)
)
)
k-Nearest Neighbors
Pipeline (
StandardScaler (
with_std=True
),
KNNClassifier (
n_neighbors=5
window_size=100
min_distance_keep=0.
weighted=True
cleanup_every=0
distance_func=functools.partial(<function minkowski_distance at 0x7f2d38a59ea0>, p=2)
softmax=False
)
)
ADWIN Bagging
[HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)]
AdaBoost
[HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)]
Bagging
[HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
)]
Leveraging Bagging
[HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)]
Stacking
[Pipeline (
StandardScaler (
with_std=True
),
SoftmaxRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=CrossEntropy (
class_weight={}
)
l2=0
)
), GaussianNB (), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), Pipeline (
StandardScaler (
with_std=True
),
KNNClassifier (
n_neighbors=5
window_size=100
min_distance_keep=0.
weighted=True
cleanup_every=0
distance_func=functools.partial(<function minkowski_distance at 0x7f2d38a59ea0>, p=2)
softmax=False
)
)]
Voting
VotingClassifier (
models=[Pipeline (
StandardScaler (
with_std=True
),
SoftmaxRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=CrossEntropy (
class_weight={}
)
l2=0
)
), GaussianNB (), HoeffdingTreeClassifier (
grace_period=200
max_depth=inf
split_criterion="info_gain"
delta=1e-07
tau=0.05
leaf_prediction="nba"
nb_threshold=0
nominal_attributes=None
splitter=GaussianSplitter (
n_splits=10
)
binary_split=False
max_size=100.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
), Pipeline (
StandardScaler (
with_std=True
),
KNNClassifier (
n_neighbors=5
window_size=100
min_distance_keep=0.
weighted=True
cleanup_every=0
distance_func=functools.partial(<function minkowski_distance at 0x7f2d38a59ea0>, p=2)
softmax=False
)
)]
use_probabilities=True
)
[baseline] Last Class
NoChangeClassifier ()
Regression
{
"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
"data": {
"url": "benchmarks/regression.csv"
},
"params": [
{
"name": "models",
"select": {
"type": "point",
"fields": [
"model"
]
},
"bind": "legend"
},
{
"name": "Dataset",
"value": "ChickWeights",
"bind": {
"input": "select",
"options": [
"ChickWeights",
"TrumpApproval"
]
}
},
{
"name": "grid",
"select": "interval",
"bind": "scales"
}
],
"transform": [
{
"filter": {
"field": "dataset",
"equal": {
"expr": "Dataset"
}
}
}
],
"repeat": {
"row": [
"MAE",
"RMSE",
"R2",
"Memory in Mb",
"Time in s"
]
},
"spec": {
"width": "container",
"mark": "line",
"encoding": {
"x": {
"field": "step",
"type": "quantitative",
"axis": {
"titleFontSize": 18,
"labelFontSize": 18,
"title": "Instance"
}
},
"y": {
"field": {
"repeat": "row"
},
"type": "quantitative",
"axis": {
"titleFontSize": 18,
"labelFontSize": 18
}
},
"color": {
"field": "model",
"type": "ordinal",
"scale": {
"scheme": "category20b"
},
"title": "Models",
"legend": {
"titleFontSize": 18,
"labelFontSize": 18,
"labelLimit": 500
}
},
"opacity": {
"condition": {
"param": "models",
"value": 1
},
"value": 0.2
}
}
}
}
Datasets
ChickWeights
Chick weights along time.
The stream contains 578 items and 3 features. The goal is to predict the weight of each chick
along time, according to the diet the chick is on. The data is ordered by time and then by
chick.
Name ChickWeights
Task Regression
Samples 578
Features 3
Sparse False
Path /home/kulbach/projects/river/river/datasets/chick-weights.csv
TrumpApproval
Donald Trump approval ratings.
This dataset was obtained by reshaping the data used by FiveThirtyEight for analyzing Donald
Trump's approval ratings. It contains 5 features, which are approval ratings collected by
5 polling agencies. The target is the approval rating from FiveThirtyEight's model. The goal of
this task is to see if we can reproduce FiveThirtyEight's model.
Name TrumpApproval
Task Regression
Samples 1,001
Features 6
Sparse False
Path /home/kulbach/projects/river/river/datasets/trump_approval.csv.gz
Models
Linear Regression
Pipeline (
StandardScaler (
with_std=True
),
LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
)
Linear Regression with l1 regularization
Pipeline (
StandardScaler (
with_std=True
),
LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=1.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
)
Linear Regression with l2 regularization
Pipeline (
StandardScaler (
with_std=True
),
LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=1.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
)
Passive-Aggressive Regressor, mode 1
Pipeline (
StandardScaler (
with_std=True
),
PARegressor (
C=1.
mode=1
eps=0.1
learn_intercept=True
)
)
Passive-Aggressive Regressor, mode 2
Pipeline (
StandardScaler (
with_std=True
),
PARegressor (
C=1.
mode=2
eps=0.1
learn_intercept=True
)
)
k-Nearest Neighbors
Pipeline (
StandardScaler (
with_std=True
),
KNNRegressor (
n_neighbors=5
window_size=100
aggregation_method="mean"
min_distance_keep=0.
distance_func=functools.partial(<function minkowski_distance at 0x7f2d38a59ea0>, p=2)
)
)
Hoeffding Tree
Pipeline (
StandardScaler (
with_std=True
),
HoeffdingTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)
)
Hoeffding Adaptive Tree
Pipeline (
StandardScaler (
with_std=True
),
HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=True
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=42
)
)
Stochastic Gradient Tree
SGTRegressor (
delta=1e-07
grace_period=200
init_pred=0.
max_depth=inf
lambda_value=0.1
gamma=1.
nominal_attributes=[]
feature_quantizer=StaticQuantizer (
n_bins=64
warm_start=100
buckets=None
)
)
Adaptive Random Forest
Pipeline (
StandardScaler (
with_std=True
),
[]
)
Adaptive Model Rules
Pipeline (
StandardScaler (
with_std=True
),
AMRules (
n_min=200
delta=1e-07
tau=0.05
pred_type="adaptive"
pred_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
splitter=TEBSTSplitter (
digits=1
)
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
fading_factor=0.99
anomaly_threshold=-0.75
m_min=30
ordered_rule_set=True
min_samples_split=5
)
)
Streaming Random Patches
Pipeline (
StandardScaler (
with_std=True
),
SRPRegressor (
model=HoeffdingTreeRegressor (
grace_period=50
max_depth=inf
delta=0.01
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
)
n_models=10
subspace_size=0.6
training_method="patches"
lam=6
drift_detector=ADWIN (
delta=1e-05
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
warning_detector=ADWIN (
delta=0.0001
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
disable_detector="off"
disable_weighted_vote=True
drift_detection_criteria="error"
aggregation_method="mean"
seed=42
metric=MAE ()
)
)
Bagging
Pipeline (
StandardScaler (
with_std=True
),
[HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=False
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
)]
)
Exponentially Weighted Average
Pipeline (
StandardScaler (
with_std=True
),
[LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
), HoeffdingAdaptiveTreeRegressor (
grace_period=200
max_depth=inf
delta=1e-07
tau=0.05
leaf_prediction="adaptive"
leaf_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
model_selector_decay=0.95
nominal_attributes=None
splitter=TEBSTSplitter (
digits=1
)
min_samples_split=5
bootstrap_sampling=True
drift_window_threshold=300
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
switch_significance=0.05
binary_split=False
max_size=500.
memory_estimate_period=1000000
stop_mem_management=False
remove_poor_attrs=False
merit_preprune=True
seed=None
), KNNRegressor (
n_neighbors=5
window_size=100
aggregation_method="mean"
min_distance_keep=0.
distance_func=functools.partial(<function minkowski_distance at 0x7f2d38a59ea0>, p=2)
), AMRules (
n_min=200
delta=1e-07
tau=0.05
pred_type="adaptive"
pred_model=LinearRegression (
optimizer=SGD (
lr=Constant (
learning_rate=0.01
)
)
loss=Squared ()
l2=0.
l1=0.
intercept_init=0.
intercept_lr=Constant (
learning_rate=0.01
)
clip_gradient=1e+12
initializer=Zeros ()
)
splitter=TEBSTSplitter (
digits=1
)
drift_detector=ADWIN (
delta=0.002
clock=32
max_buckets=5
min_window_length=5
grace_period=10
)
fading_factor=0.99
anomaly_threshold=-0.75
m_min=30
ordered_rule_set=True
min_samples_split=5
)]
)
River MLP
Pipeline (
StandardScaler (
with_std=True
),
MLPRegressor (
hidden_dims=(5,)
activations=(<class 'river.neural_net.activations.ReLU'>, <class 'river.neural_net.activations.ReLU'>, <class 'river.neural_net.activations.Identity'>)
loss=Squared ()
optimizer=SGD (
lr=Constant (
learning_rate=0.001
)
)
seed=42
)
)
[baseline] Mean predictor
StatisticRegressor (
statistic=Mean ()
)
Environment
Python implementation: CPython
Python version : 3.9.16
IPython version : 8.11.0
river : 0.15.0
numpy : 1.24.2
scikit-learn: 1.2.1
pandas : 1.5.3
scipy : 1.10.1
Compiler : GCC 11.3.0
OS : Linux
Release : 5.15.0-1033-azure
Machine : x86_64
Processor : x86_64
CPU cores : 2
Architecture: 64bit