text_html_output_1.png
from sklearn import metrics

from sklearn.metrics import accuracy_score

import numpy as np

import pandas as pd

mnist_train = pd.read_csv('../input/mnist-in-csv/mnist_train.csv')
mnist_test = pd.read_csv('../input/mnist-in-csv/mnist_test.csv')

X_train = mnist_train.iloc[:, 1:785]
y_train = mnist_train.iloc[:, 0]
lda = LDA(n_components=9)
X_train_r2 = lda.fit(X_train, y_train)

X_test = mnist_test.iloc[:, 1:785]
y_test = mnist_test.iloc[:, 0]

y_pred = lda.predict(X_test)

w = lda.coef_
w.shape

w0 = lda.intercept_
np.transpose(w0).shape

print(f'Classification report for classifier {lda}:\n{metrics.classification_report(y_test, y_pred)}\n')