1. Dataset
Train
Test
x_train = train.drop(['Diabetes'], axis=1)
y_train = train['Diabetes']
x_test = test
2. LDA
# LDA
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.metrics import accuracy_score
cld = LinearDiscriminantAnalysis()
cld.fit(x_train, y_train)
y_train_pred = cld.predict(x_train)
y_test_cld_pred = cld.predict(x_test)
print(accuracy_score(y_train, y_train_pred))
3. QDA
# QDA
from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis
from sklearn.metrics import accuracy_score
cqd=QuadraticDiscriminantAnalysis()
cqd.fit(x_train, y_train)
y_train_pred = cqd.predict(x_train)
y_test_cqd_pred = cqd.predict(x_test)
print(accuracy_score(y_train, y_train_pred))
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