y_hat=regr.predict(test[['close','RSI','SMA','EMA','MACD','vloum']])
x=np.asanyarray(test[['close','RSI','SMA','EMA','MACD','vloum']])
y=np.asanyarray(test[['nextPr']])
print("Residual sum of squares: %.2f"
%np.mean((y_hat-y) **2))
# Explained variance score: 1 is perfect prediction
print('Variance score: %.2f'%regr.score(x, y))