How to Connect Model Input Data With Predictions for Machine Learning

Last Updated on August 19, 2020

Fitting a model to a training dataset is so easy today with libraries like scikit-learn.

A model can be fit and evaluated on a dataset in just a few lines of code. It is so easy that it has become a problem.

The same few lines of code are repeated again and again and it may not be obvious how to actually use the model to make a prediction. Or, if a prediction is made, how to relate the predicted values to the actual input values.

I know that this is the case because I get many emails with the question:

How do I connect the predicted values with the input data?

This a common problem.

In this tutorial, you will discover how to relate the predicted values with the inputs to a machine learning model.

After completing this tutorial, you will know:

• How to fit and evaluate the model on a training dataset.
• How to use the fit model to make predictions one at a time and in batches.
• How to connect the predicted values with the inputs to the model.

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