| // Licensed to the Apache Software Foundation (ASF) under one or more |
| // contributor license agreements. See the NOTICE file distributed with |
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| = Introduction |
| |
| Regression is a ML algorithm that can be trained to predict real numbered outputs, like temperature, stock price, etc. Regression is based on a hypothesis that can be linear, quadratic, polynomial, non-linear, etc. The hypothesis is a function that is based on some hidden parameters and the input values. |
| |
| All existing training algorithms presented in this section are designed to solve regression tasks: |
| |
| * Linear Regression |
| * Decision Trees Regression |
| * k-NN Regression |
