The role of co-variance matrix in Principal component analysis is to find _____________________ * To visualize the data The relationship between the variables under study. For finding the outliers. To check for accuracy in the data displayed code example
Example: pca
#if required,do pca 1st
#then outliers removal then skewness removal
from sklearn.decomposition import PCA
pca=PCA(n_components=20)
pca.fit(df)
x_pca=pca.transform(df)
print(x_pca.shape)
x_pca20=pd.DataFrame(data=x_pca)
x_pca20