Kernel Entropy Component Analysis in Python

kernel_eca is a Python implementation of the Kernel Entropy Component Analysis, build to be compatible with scikit-learn. It can be installed with pip.

pip install kernel_eca



In [2]:

    
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt

from kernel_eca import KernelECA
from sklearn.decomposition.kernel_pca import KernelPCA

from sklearn.datasets import make_circles
X,y = make_circles(n_samples=300, noise=0.05, factor=0.3, random_state=571)

kpca = KernelPCA(n_components=2, kernel= "rbf",gamma=10)
X_kpca = kpca.fit_transform(X)

keca = KernelECA(n_components=2, kernel= "rbf",gamma=10)
X_keca = keca.fit_transform(X)

plt.figure()
plt.subplot(2, 2, 1, aspect='equal')
plt.title("Original space")
reds = y == 0
blues = y == 1

plt.plot(X[reds, 0], X[reds, 1], "ro")
plt.plot(X[blues, 0], X[blues, 1], "bo")
plt.xlabel("$x_1$")
plt.ylabel("$x_2$")

X1, X2 = np.meshgrid(np.linspace(-1.5, 1.5, 50), np.linspace(-1.5, 1.5, 50))
X_grid = np.array([np.ravel(X1), np.ravel(X2)]).T
# projection on the first principal component (in the phi space)
Z_grid = kpca.transform(X_grid)[:, 0].reshape(X1.shape)
plt.contour(X1, X2, Z_grid, colors='grey', linewidths=1, origin='lower')

plt.subplot(2, 2, 2, aspect='equal')
plt.plot(X_kpca[reds, 0], X_kpca[reds, 1], "ro")
plt.plot(X_kpca[blues, 0], X_kpca[blues, 1], "bo")
plt.title("Projection by KPCA")
plt.xlabel("1st principal component")
plt.ylabel("2nd component")

plt.subplot(2, 2, 3, aspect='equal')
plt.plot(X_keca[reds, 0], X_keca[reds, 1], "ro")
plt.plot(X_keca[blues, 0], X_keca[blues, 1], "bo")
plt.title("Projection by KECA")
plt.xlabel("1st principal component in space induced by $\phi$")
plt.ylabel("2nd component")

plt.subplot(2, 2, 4, aspect='equal')
plt.plot(X[reds, 0], X[reds, 1], "ro")
plt.plot(X[blues, 0], X[blues, 1], "bo")
plt.title("Original space after inverse transform")
plt.xlabel("$x_1$")
plt.ylabel("$x_2$")

plt.subplots_adjust(0.02, 0.10, 0.98, 0.94, 0.04, 0.35)
plt.show()









    



---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
<ipython-input-2-63d9d7cce116> in <module>()
      3 import matplotlib.pyplot as plt
      4 
----> 5 from kernel_eca import KernelECA
      6 from sklearn.decomposition.kernel_pca import KernelPCA
      7 

ImportError: No module named 'kernel_eca'