Calculating Multivariate regression using TensorFlow
问题 I am trying to implement a Multivariate regression in tensorflow where I have 192 examples with 6 features and one output variable. From my model I get a matrix (192, 6) while it should be (192, 1). Does anybody know what is wrong with my code? I provided my code below. # Parameters learning_rate = 0.0001 training_epochs = 50 display_step = 5 train_X = Data_ABX3[0:192, 0:6] train_Y = Data_ABX3[0:192, [24]] # placeholders for a tensor that will be always fed. X = tf.placeholder('float', shape