Python

Search

PCA in sklearn

import numpy as np
from sklearn.decomposition import PCA
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
pca = PCA(n_components=2)
pca.fit(X)

print(pca.explained_variance_ratio_)

print(pca.singular_values_)

Comment

PREVIOUS	NEXT

Code Example
Python :: tkinter background color
Python :: import forms
Python :: python get time milliseconds
Python :: datetime one week ago python
Python :: get the number of today week python
Python :: decisiontreeclassifier sklearn
Python :: how to count stopwords in df
Python :: How to check how much time elapsed Python
Python :: colab tqdm import
Python :: pyspark create empty dataframe
Python :: python day number from date
Python :: python except show error
Python :: upgrade python to 3.8
Python :: convert dataframe column to float
Python :: reduced fraction python
Python :: django queryset average of unique values
Python :: add self role with discord bot python
Python :: remove unicode from string python
Python :: Function to a button in tkinter
Python :: python how to get script directory
Python :: python program to print list vertically without using loop
Python :: tkinter execute function on enter
Python :: RandomForestRegressor import
Python :: django jinja subset string
Python :: get ip from request django
Python :: python convert list to dict with index
Python :: scikit learn ridge classifier
Python :: python return -1
Python :: python blackjack
Python :: rvec tvec ros message

Search

PYTHON

PCA in sklearn

ADD CONTENT