Machine Learning With Go

Docker-izing model predictions

As with the training of our model, we are going to utilize command line arguments to specify the input directories and output directories utilized by our prediction program. This time we will have two input directories; one for the persisted model and one for a directory that will contain attributes from which we are to make predictions. Our program will, thus, do the following:

1. Read in the model from the model input directory.

 

 

2. Walk over files in the attributes input directory.
3. For each file in the attributes input directory (containing attributes with no corresponding prediction of disease progression), utilize our loaded model to make a prediction of disease progression.
4. Output the disease progression ...