Partial dependence plots show the dependence between the target function

This example shows that imputing the missing values can give better results than discarding the samples containing any missing value. Imputing

Three different types of SVM-Kernels are displayed below. The polynomial and RBF are especially useful when the data-points are not linearly separable.

Estimates Lasso and Elastic-Net regression models on a manually generated sparse signal corrupted with an additive noise. Estimated coefficients are

An example using IsolationForest for anomaly detection. The IsolationForest ?isolates? observations by randomly selecting a feature and then randomly selecting

Principal Component Analysis applied to the Iris dataset. See

An example to show covariance estimation with the Mahalanobis distances on Gaussian distributed data. For Gaussian distributed

When the amount of contamination is known, this example illustrates three different ways of performing

Shows how shrinkage improves classification.

The