November 2019
Intermediate to advanced
346 pages
9h 36m
English
In this section, we'll walk through a recipe showing how to use PCA on data:
from sklearn.decomposition import PCAimport pandas as pddata = pd.read_csv("file_pe_headers.csv", sep=",")X = data.drop(["Name", "Malware"], axis=1).to_numpy()
from sklearn.preprocessing import StandardScalerX_standardized = StandardScaler().fit_transform(X)
pca = PCA()pca.fit_transform(X_standardized)
print(pca.explained_variance_ratio_)
The following screenshot shows the ...