Breaking News: Grepper is joining You.com. Read the official announcement!

dimension reduction using pca

josh.ipynb answered on June 9, 2022 Popularity 8/10 Helpfulness 3/10

answer dimension reduction using pca

dimension reduction using pca

Comment

# Import PCA
from sklearn.decomposition import PCA

# Create a PCA instance with 2 components: pca
pca = PCA(n_components= ...)

# Fit the PCA instance to the scaled samples
pca.fit(scaled_samples)

# Transform the scaled samples: pca_features
pca_features = pca.transform(scaled_samples)

# Print the shape of pca_features
print(pca_features.shape)

Popularity 8/10 Helpfulness 3/10 Language python

Source: campus.datacamp.com

Tags: dimension-reduction pca python using

Link to this answer
Share Copy Link