Plot Stochastic Linear Adaptative Neuron Classifier

visualizes the mini-batch by applying batch gradient descent to a smaller subset of test data.

# Author: L.Kouadio
# Licence: BSD-3-clause

fetch data and uses the preprocessed

import matplotlib.pyplot as plt
from watex.base import AdalineStochasticGradientDescent
from watex.analysis import decision_region
from watex.datasets import fetch_data
X, y = fetch_data ('bagoue prepared data')

fig, axe = plt.subplots (1, 2)
asgd= AdalineStochasticGradientDescent (n_iter=15, eta=.01).fit(X.toarray(), y )
decision_region(X.toarray(), y, clf=asgd, return_axe=True, axe= axe[0]) # test set view
axe[0].set_title ("Adaline - Stochastic Gradient descent")

axe[1].plot(range (1, len(asgd.cost_) +1 ), asgd.cost_, marker ="o")
axe[1].set_xlabel ("Epochs")
axe[1].set_ylabel ("Sum-squared-error")
plt.tight_layout()
plt.show()

/home/docs/checkouts/readthedocs.org/user_builds/watex/checkouts/0.2.1/watex/analysis/decomposition.py:256: UserWarning:

You passed a edgecolor/edgecolors ('black') for an unfilled marker ('x').  Matplotlib is ignoring the edgecolor in favor of the facecolor.  This behavior may change in the future.