def k_nearst_neighbour_classify(self):
knn = KNNClassifier()
predictions = knn.predict_classification(self.X_train, self.y_train,
self.X_test)
accuracy = str(self.main.accuracy(self.y_test, predictions))
accuracy = accuracy[0:4]
self.knn_acc_label.setText(accuracy)
def classify_custom_input(self, custom_input_vector):
nb = NaiveBayesClassifier()
nb.train(self.X_train, self.y_train)
prediction = nb.predict([custom_input_vector])
self.custom_text_nb_label.setText(str(prediction[0]))
knn = KNNClassifier()
prediction = knn.predict_classification(self.X_train, self.y_train,
[custom_input_vector])
self.custom_text_knn_label.setText(str(prediction[0]))
rf = SklearnRandomForest()
prediction = rf.random_forest(self.X_train, self.y_train,
[custom_input_vector])
self.custom_text_dt_label.setText(str(prediction[0]))
dt = SklearnDecisionTree()
prediction = dt.decision_tree(self.X_train, self.y_train,
[custom_input_vector])
self.custom_text_rf_label.setText(str(prediction[0]))