visualize lda

Author: lazyprogrammer

logistic_regression_class/logistic_visualize.py

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+# visualizes the Bayes solution
+#
+# the notes for this class can be found at: 
+# https://www.udemy.com/data-science-logistic-regression-in-python
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+N = 100
+D = 2
+
+
+X = np.random.randn(N,D)
+
+# center the first 50 points at (-2,-2)
+X[:50,:] = X[:50,:] - 2*np.ones((50,D))
+
+# center the last 50 points at (2, 2)
+X[50:,:] = X[50:,:] + 2*np.ones((50,D))
+
+# labels: first 50 are 0, last 50 are 1
+T = np.array([0]*50 + [1]*50)
+
+# add a column of ones
+ones = np.array([[1]*N]).T
+Xb = np.concatenate((ones, X), axis=1)
+
+def sigmoid(z):
+    return 1/(1 + np.exp(-z))
+
+# get the closed-form solution
+w = np.array([0, 4, 4])
+
+# calculate the model output
+z = Xb.dot(w)
+Y = sigmoid(z)
+
+plt.scatter(X[:,0], X[:,1], c=T, s=100, alpha=0.5)
+
+x_axis = np.linspace(-6, 6, 100)
+y_axis = -x_axis
+plt.plot(x_axis, y_axis)
+plt.show()