Mastering Machine Learning for Penetration Testing

Linear discriminant analysis

In previous chapters, especially in Chapter 1, Introduction to Machine Learning in Pen Testing, we saw the statistical procedure of principal component analysis (PCA). Linear discriminant analysis (LDA) is a dimensionality reduction technique, as well. It is used to find a linear combination of features that separate classes:

To use LDA with scikit-learn, import it with this line:

from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA

Use it as follows:

sklearn_lda = LDA(n_components=2) X_lda_sklearn = sklearn_lda.fit_transform(X, y)