b4db36d337a4ff83f1bcb37c5a8c615d3134d372,examples/covariance/plot_mahalanobis_distances.py,,,#,55

Before Change


    of America, 17, 684-688.


print(__doc__)

import numpy as np
import matplotlib.pyplot as plt

After Change


// boxplots. The distribution of outlier samples is more separated from the
// distribution of inlier samples for robust MCD based Mahalanobis distances.

fig, (ax1, ax2) = plt.subplots(1, 2)
plt.subplots_adjust(wspace=.6)

// Calculate cubic root of MLE Mahalanobis distances for samples
emp_mahal = emp_cov.mahalanobis(X - np.mean(X, 0)) ** (0.33)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 3

Instances


Project Name: scikit-learn/scikit-learn
Commit Name: b4db36d337a4ff83f1bcb37c5a8c615d3134d372
Time: 2020-05-20
Author: jliu176@gmail.com
File Name: examples/covariance/plot_mahalanobis_distances.py
Class Name:
Method Name:


Project Name: scikit-learn/scikit-learn
Commit Name: 45a6ef7b722811ff1dfdc76652a144190c9e0ef8
Time: 2020-06-15
Author: madhura@predictivehire.com
File Name: examples/inspection/plot_partial_dependence.py
Class Name:
Method Name:


Project Name: nipy/dipy
Commit Name: 1fc1166b0b36d063d2c4d1807843e56a6f0a59f4
Time: 2013-11-02
Author: arokem@gmail.com
File Name: doc/examples/restore_dti.py
Class Name:
Method Name: