Lda scikit learn

import numpy as np
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
y = np.array([1, 1, 1, 2, 2, 2])
clf = LinearDiscriminantAnalysis()
clf.fit(X, y)

print(clf.predict([[-0.8, -1]]))

Source: scikit-learn.org

Scikit learn lda

from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
lda = LDA(n_components = 2)
X_train = lda.fit_transform(X_train, y_train)
X_test = lda.transform(X_test)

Similar codes

0 vote128 views1 answer
Concatenate dataframes using one column
Python
29 votes116 views5 answers
Python date and time
Python
0 vote117 views1 answer
Python min length list of strings
Python
0 vote125 views1 answer
Resize cmd using python
Python
0 vote132 views1 answer
Pandas dataframe caption
Python
32 votes123 views4 answers
Copy to clipboard python
Python
0 vote119 views1 answer
Request.build_absolute_uri django
Python
1 vote135 views1 answer
Python convert list of lists of strings to int
Python
0 vote121 views1 answer
Fix the debug_mode = false django
Python
0 vote105 views1 answer
How to get what type of file a file is in python
Python