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

from sklearn.decomposition import PCA
pca = PCA(n_components=2)
X_train = pca.fit_transform(X_train)
X_test = pca.transform(X_test)

Pca python

from sklearn.decomposition import PCA

pca = PCA(n_components=3)
pca.fit(features)
features_pca = pca.transform(features)
print("original shape:   ", features.shape)
print("transformed shape:", features_pca.shape)
print(pca.explained_variance_)
print(pca.explained_variance_ratio_)

Scikit learn pca

from sklearn.decomposition import KernelPCA
kpca = KernelPCA(n_components = 2, kernel = 'rbf')
X_train = kpca.fit_transform(X_train)
X_test = kpca.transform(X_test)

Similar codes

5 votes108 views1 answer
Python matplt
Python
0 vote118 views2 answers
How to make a time limit using renpy
Python
3 votes112 views1 answer
Make a window tkinter
Python
0 vote113 views1 answer
Fix misspelled in Wikipedia library on python
Python
7 votes101 views5 answers
How to multiply two lists in python
Python
68 votes113 views6 answers
Create folders in python
Python
6 votes121 views3 answers
If you have the following data structure, which of the following evaluates to 8? array = [[5,4,2],[4,4,1],[8,9,0],3];
Python
0 vote112 views1 answer
Python class optional attributes
Python
2 votes77 views1 answer
Check substring in pandas column
Python
9 votes151 views2 answers
Default flask app
Python Flask