def run_nb(X_train, y_train, X_test, y_test): nb = GaussianNB() nb.fit(X_train, y_train) return compute_accuracy(y_test, nb.predict(X_test))
def run_linearDiscriminantAnalysis_full(X, y):
from learner.LinearDiscriminantAnalysis import LinearDiscriminantAnalysis
lda = LinearDiscriminantAnalysis(n_components=1)
lda.fit(X, y)
return compute_accuracy(y, lda.predict(X))
def run_sk_linearDiscriminantAnalysis_full(X, y):
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
lda = LinearDiscriminantAnalysis(n_components=1, solver='eigen')
lda.fit(X, y)
return compute_accuracy(y, lda.predict(X))
def run_sk_linearDiscriminantAnalysis(X_train, y_train, X_test, y_test):
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
lda = LinearDiscriminantAnalysis(n_components=1)
lda.fit(X_train, y_train)
return compute_accuracy(y_train, lda.predict(X_train)), compute_accuracy(
y_test, lda.predict(X_test))