The friendly neighbor approach to machine learninglabels, predictions, accuracies = list(y_test), , k_list = for k in k_list:knn_clf = KNeighborsClassifier(n_neighbors=k)knn_clf.fit(X_train, y_train)y_pred = knn_clf.predict(X_test)predictions.append(list(y_pred))accuracies.append(accuracy_score(y_test, y_pred).round(4)*100)df_predictions = pd.DataFrame({'Label': labels})for k, pred in zip(k_list, predictions):df_predictions = preddf_accuracies...
The category neighborhood of a dataset will be learned using soft nearest neighbor lossIn this text, we discuss easy methods to implement the soft nearest neighbor loss which we also talked about here.Representation learning...