NesterovMomentum

Nesterov Momentum optimizer.

Parameters

• lr – defaults to 0.1

• rho – defaults to 0.9

Attributes

• learning_rate

Examples

>>> from river import datasets
>>> from river import evaluate
>>> from river import linear_model
>>> from river import metrics
>>> from river import optim
>>> from river import preprocessing

>>> dataset = datasets.Phishing()
>>> optimizer = optim.NesterovMomentum()
>>> model = (
...     preprocessing.StandardScaler() |
...     linear_model.LogisticRegression(optimizer)
... )
>>> metric = metrics.F1()

>>> evaluate.progressive_val_score(dataset, model, metric)
F1: 84.29%

Methods

look_ahead

Updates a weight vector before a prediction is made.

Parameters: w (dict): A dictionary of weight parameters. The weights are modified in-place. Returns: The updated weights.

Parameters

• w ('dict')

step

Updates a weight vector given a gradient.

Parameters

• w ('dict | VectorLike')
• g ('dict | VectorLike')

Returns

dict | VectorLike: The updated weights.