LeaveOutClusterCV

class mastml.data_splitters.LeaveOutClusterCV(cluster, **kwargs)

Bases: mastml.data_splitters.BaseSplitter

Class to generate train/test split using clustering. Args:

cluster: clustering method from sklearn.cluster used to generate train/test split kwargs: takes in any other key argument for optional cluster parameters

Methods:

get_n_splits: method to calculate the number of splits to perform across all splitters

Args:

X: (numpy array), array of X features y: (numpy array), array of y data groups: (numpy array), array of group labels

Returns:

(int), number of splits

split: method to perform split into train indices and test indices

Args:

X: (numpy array), array of X features y: (numpy array), array of y data groups: (numpy array), array of group labels

Returns:

(numpy array), array of train and test indices

labels: method that returns cluster labels of X features

Args:

X: (numpy array), array of X features y: (numpy array), array of y data groups: (numpy array), array of group labels

Returns:

(numpy array), array of cluster labels

Methods Summary

get_n_splits(X[, y, groups])	Returns the number of splitting iterations in the cross-validator
labels(X[, y, groups])
split(X[, y, groups])	Generate indices to split data into training and test set.

Methods Documentation

get_n_splits(X, y=None, groups=None)

Returns the number of splitting iterations in the cross-validator

labels(X, y=None, groups=None)

split(X, y=None, groups=None)

Generate indices to split data into training and test set.

X : array-like of shape (n_samples, n_features)

Training data, where n_samples is the number of samples and n_features is the number of features.

y : array-like of shape (n_samples,)

The target variable for supervised learning problems.

groups : array-like of shape (n_samples,), default=None

Group labels for the samples used while splitting the dataset into train/test set.

train : ndarray

The training set indices for that split.

test : ndarray

The testing set indices for that split.