pca python
import numpy as np
from sklearn.decomposition import PCA
pca = PCA(n_components = 3) # Choose number of components
pca.fit(X) # fit on X_train if train/test split applied
print(pca.explained_variance_ratio_)pca python
import numpy as np
from sklearn.decomposition import PCA
pca = PCA(n_components = 3) # Choose number of components
pca.fit(X) # fit on X_train if train/test split applied
print(pca.explained_variance_ratio_)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_pca20Copyright © 2021 Codeinu
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