#Java-based machine learning examples
This project includes non-productive example code for illustration purposes.
| class | description |
|---|---|
| LinearRegressionFunction | Implements a straightforward, rudimentary linear regression function. This class includes a main method also which shows how to use it. |
| Cost | Determines the cost of an concrete linear regression function instance. |
| Leaner | Trains/improves a linear regression function by creating a new improved instance. This class implements a gradient descent algorithm. |
| FunctionUnderfittingExample | Shows how to train a linear regression function based on test data. The resulting function underfits caused by the low number of features |
| FunctionBalancedExample | Shows how to train a balanced linear regression function based on test data. |
| FunctionOverfittingExample | Shows how to train a overfitting linear regression function based on test data. |