watex.analysis.compute_scores

watex.analysis.compute_scores(X, n_features, n_components=5)

Compute PCA score and Factor Analysis scores from training X.

Parameters:

• X (Ndarray of shape ( M x N), \(M=m-samples\) & \(N=n-features\)) – training set; Denotes data that is observed at training and prediction time, used as independent variables in learning. The notation is uppercase to denote that it is ordinarily a matrix. When a matrix, each sample may be represented by a feature vector, or a vector of precomputed (dis)similarity with each training sample. X may also not be a matrix, and may require a feature extractor or a pairwise metric to turn it into one before learning a model.

• n_features (int,) – number of features that composes X

• n_components (int, default {5}) – number of component to retrieve.

Returns:

Scores from PCA and FA from transformed X

Return type:

Tuple (pca_scores, fa_scores)