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River
Model evaluation
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online-ml/river
Introduction 🍼
Recipes 🌮
API reference 🍱
Examples 🌶️
FAQ
Releases
Benchmarks
River
online-ml/river
Introduction 🍼
Introduction 🍼
Installation
Basic concepts
Getting started
Why use River?
Next steps
Related projects
Recipes 🌮
Recipes 🌮
Reading data
Model evaluation
Pipelines
Feature extraction
Hyperparameter tuning
Mini-batching
Incremental decision trees in river: the Hoeffding Tree case
Active learning
Multi-armed bandits
Cloning and mutating
Rolling computations
API reference 🍱
API reference 🍱
Overview
active
anomaly
bandit
base
cluster
compat
compose
conf
covariance
datasets
drift
dummy
ensemble
evaluate
facto
feature_extraction
feature_selection
forest
imblearn
linear_model
metrics
misc
model_selection
multiclass
multioutput
naive_bayes
neighbors
neural_net
optim
preprocessing
proba
reco
rules
sketch
stats
stream
time_series
tree
utils
Examples 🌶️
Examples 🌶️
From batch to online/stream
Bike-sharing forecasting
Building a simple nowcasting model
Content personalization
Debugging a pipeline
Working with imbalanced data
Handling uncertainty with quantile regression
Sentence classification
The art of using pipelines
Matrix factorization for recommender systems
FAQ
FAQ
Releases
Releases
0.20.1 - 2023-11-09
0.20.0 - 2023-11-09
0.19.0 - 2023-08-02
0.18.0 - 2023-06-26
0.17.0 - 2023-05-27
0.16.0 - 2023-05-08
0.15.0 - 2023-01-29
0.14.0 - 2022-10-26
0.13.0 - 2022-09-15
0.12.1 - 2022-09-02
0.12.0 - 2022-09-02
0.11.1 - 2022-06-06
0.11.0 - 2022-05-28
0.10.1 - 2022-02-05
0.10.0 - 2022-02-04
0.9.0 - 2021-11-30
0.8.0 - 2021-08-31
0.7.1 - 2021-06-13
0.7.0 - 2021-04-16
0.6.1 - 2020-06-10
0.6.0 - 2020-06-09
0.5.1 - 2020-03-29
0.5.0 - 2020-03-13
0.4.4 - 2019-11-11
0.4.3 - 2019-10-27
0.4.1 - 2019-10-23
0.3.0 - 2019-06-23
0.2.0 - 2019-05-27
0.1.0 - 2019-05-08
0.0.3 - 2019-03-21
0.0.2 - 2019-02-13
Benchmarks
Benchmarks
Binary classification
Multiclass classification
Regression
Model evaluation
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