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File Content: `plot_logistic.py`

#!/usr/bin/python
# -*- coding: utf-8 -*-


"""
=========================================================
Logistic function
=========================================================

Shown in the plot is how the logistic regression would, in this
synthetic dataset, classify values as either 0 or 1,
i.e. class one or two, using the logistic curve.

"""
print(__doc__)


# Code source: Gael Varoquaux
# License: BSD 3 clause

import numpy as np
import matplotlib.pyplot as plt

from sklearn import linear_model

# this is our test set, it's just a straight line with some
# Gaussian noise
xmin, xmax = -5, 5
n_samples = 100
np.random.seed(0)
X = np.random.normal(size=n_samples)
y = (X > 0).astype(np.float)
X[X > 0] *= 4
X += .3 * np.random.normal(size=n_samples)

X = X[:, np.newaxis]
# run the classifier
clf = linear_model.LogisticRegression(C=1e5)
clf.fit(X, y)

# and plot the result
plt.figure(1, figsize=(4, 3))
plt.clf()
plt.scatter(X.ravel(), y, color='black', zorder=20)
X_test = np.linspace(-5, 10, 300)


def model(x):
    return 1 / (1 + np.exp(-x))
loss = model(X_test * clf.coef_ + clf.intercept_).ravel()
plt.plot(X_test, loss, color='red', linewidth=3)

ols = linear_model.LinearRegression()
ols.fit(X, y)
plt.plot(X_test, ols.coef_ * X_test + ols.intercept_, linewidth=1)
plt.axhline(.5, color='.5')

plt.ylabel('y')
plt.xlabel('X')
plt.xticks(range(-5, 10))
plt.yticks([0, 0.5, 1])
plt.ylim(-.25, 1.25)
plt.xlim(-4, 10)
plt.legend(('Logistic Regression Model', 'Linear Regression Model'),
           loc="lower right", fontsize='small')
plt.show()

Name	Size	Permission
README.txt	135 bytes	0644
lasso_dense_vs_sparse_data.py	1862 bytes	0644
plot_ard.py	2828 bytes	0644
plot_bayesian_ridge.py	2733 bytes	0644
plot_huber_vs_ridge.py	2206 bytes	0644
plot_iris_logistic.py	1679 bytes	0644
plot_lasso_and_elasticnet.py	2074 bytes	0644
plot_lasso_coordinate_descent_path.py	2945 bytes	0644
plot_lasso_lars.py	1080 bytes	0644
plot_lasso_model_selection.py	5431 bytes	0644
plot_logistic.py	1568 bytes	0644
plot_logistic_l1_l2_sparsity.py	2601 bytes	0644
plot_logistic_multinomial.py	2480 bytes	0644
plot_logistic_path.py	1195 bytes	0644
plot_multi_task_lasso_support.py	2319 bytes	0644
plot_ols.py	1936 bytes	0644
plot_ols_3d.py	2040 bytes	0644
plot_ols_ridge_variance.py	2060 bytes	0644
plot_omp.py	2263 bytes	0644
plot_polynomial_interpolation.py	2088 bytes	0644
plot_ransac.py	1859 bytes	0644
plot_ridge_coeffs.py	2785 bytes	0644
plot_ridge_path.py	2138 bytes	0644
plot_robust_fit.py	3050 bytes	0644
plot_sgd_comparison.py	1819 bytes	0644
plot_sgd_iris.py	2202 bytes	0644
plot_sgd_loss_functions.py	1232 bytes	0644
plot_sgd_penalties.py	1877 bytes	0644
plot_sgd_separating_hyperplane.py	1221 bytes	0644
plot_sgd_weighted_samples.py	1458 bytes	0644
plot_sparse_recovery.py	7486 bytes	0644
plot_theilsen.py	3846 bytes	0644

File Content: plot_logistic.py

File Content: `plot_logistic.py`