def determistic_eval(train_path,test_path,svm=False): train=dataset.labeled_to_dataset(train_path) test=dataset.labeled_to_dataset(test_path) if(svm): svm_opt=OptimizedSVM() else: svm_opt=OptimizedRandomForest() clf = RandomForestClassifier(n_estimators=500) #clf=svm_opt.grid_search(train.X,train.y,n_split=2) #clf=svm_opt.predefined_search(train.X,train.y) #eval_train(clf) print(train.y) clf = clf.fit(train.X, train.y) eval_test(test.X,test.y,clf)
def show_labeled(path,reduction_id,tabu=[]): data=dataset.labeled_to_dataset(path)#annotated_to_dataset(path) tsne_X=reductions[reduction_id](data) tsne_data=dataset.LabeledDataset(tsne_X,data.y) plot.labeled_plot2D(tsne_data,tabu)