model = OneClassSVM(kernel='rbf')
model.fit(X_train)
#model.fit(X_test)
y_train = model.predict(X_train)
y_test = model.predict(X_test)
y_ndata = model.predict(X_data)

#number of anomalies
train = y_train[y_train == 1].size
test = y_test[y_train == 1].size
print("Size of inliers in Train set:", train)
print("Size of inliers in Test set:", test)
print("Size of inliers in Real data:", y_ndata[y_ndata == 1].size)

train_anomaly = y_train[y_train == -1].size
test_anomaly = y_train[y_train == -1].size
print("Size of outliers in Train set:", train_anomaly)
print("Size of outliers in Test set:", test_anomaly)
print("Size of outliers in Real data:", y_ndata[y_ndata == -1].size)