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)
