How to scale prediction back after preprocessing
When you decided you have to scale your data, you usually have to follow these steps:

For training:


Scale / Standarize the training set
Store the scaling / standarization factors of the training set
Train the model


For predicting:


Scale / standarize the input data, but very important, with the scaling/standarization factors stored during the training process. You dont have to compute the min, max or mean values of the new data.
Predict


The reason is that you have to map the new data to the same feature-space used for the training process, so you have to scale/std it with the same factors, otherwise, you are changing the feature space.