from pybrain.tools.validation import testOnSequenceData
from sklearn.neighbors import KNeighborsClassifier
from pylab import figure, ioff, clf, contourf, ion, draw, show
from pybrain.structure.modules import LSTMLayer, SoftmaxLayer
from pybrain.datasets import SequenceClassificationDataSet
from pybrain.supervised import RPropMinusTrainer,BackpropTrainer
from sklearn.cross_validation import train_test_split,StratifiedKFold
from os.path import exists
from pybrain.tools.customxml.networkwriter import NetworkWriter
from pybrain.tools.customxml.networkreader import NetworkReader
from sklearn.metrics import precision_score,recall_score,accuracy_score,f1_score,roc_auc_score
# Creating training and test data
DS = common.generate_ucf_dataset('frames')
X, y = DS
# metric vars
precision= []
recall = []
f1 = []
accuracy = []
# Using stratified cross-validation
stf = StratifiedKFold(y, n_folds=10)
for train_index, test_index in stf:
X_train = []
X_test = []
y_train = []
