# Copyright 2021 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# or in the "license" file accompanying this file. This file is distributed
# on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
# express or implied. See the License for the specific language governing
# permissions and limitations under the License.
import numpy as np
from sklearn.neural_network import MLPClassifier
[docs]
class MLP:
def __init__(
self,
n_inputs: int,
n_hidden: int = 32,
epochs: int = 100,
learning_rate: float = 1e-3,
activation: str = "relu",
):
self.n_inputs = n_inputs
self.n_hidden = n_hidden
self.epochs = epochs
self.learning_rate = learning_rate
self.model = MLPClassifier(
activation=activation, hidden_layer_sizes=(n_hidden,)
)
[docs]
def fit(self, X, y):
self.model.fit(X, y)
[docs]
def predict_proba(self, X):
return self.model.predict_proba(X)
[docs]
def predict(self, X):
return np.round(self.predict_proba(X))