Note
Click here to download the full example code
Binary Targets with SIRΒΆ
Sliced Inverse Regression is able to find a one-dimensional subspace that seperates cases in the famous breast cancer dataset.
import matplotlib.pyplot as plt
from sklearn.datasets import load_breast_cancer
from sliced import SlicedInverseRegression
X, y = load_breast_cancer(return_X_y=True)
sir = SlicedInverseRegression(n_directions=2).fit(X, y)
X_sir = sir.transform(X)
plt.scatter(X_sir[:, 0], X_sir[:, 1], c=y, alpha=0.8, edgecolor='k')
plt.xlabel("$X\hat{\\beta}_{1}$")
plt.ylabel("$X\hat{\\beta}_{2}$")
plt.title("Breast Cancer Data")
plt.show()
Total running time of the script: ( 0 minutes 0.376 seconds)