import numpy as np
import tensorflow as tf
import skflow
x_train = np.array([[1], [2], [3], [4]])
y_train = np.array([[2], [4], [6], [8]])
linear_regressor = skflow.LinearRegressor(feature_columns=[tf.contrib.layers.real_valued_column("", dimension=1)])
linear_regressor.fit(X=x_train, y=y_train, steps=1000)
x_test = np.array([[5], [6]])
predictions = list(linear_regressor.predict(x_test))
for i, p in enumerate(predictions):
