While there are several regression model types available in the machine learning eco-system, there are two primary regression models groups: linear and logistic, both of which have rich implementations in ML.NET.
ML.NET provides the following linear regression trainers:
- FastTreeRegressionTrainer
- FastTreeTweedieTrainer
- FastForestRegressionTrainer
- GamRegressionTrainer
- LbfgsPoissonRegressionTrainer
- LightGbmRegressionTrainer
- OlsTrainer
- OnlineGradientDescentTrainer
- SdcaRegressionTrainer
The employee attrition application we will be creating later in this chapter utilizes the linear regression SDCA trainer.
In addition, ML.NET provides the following binary logistic regression trainers:
- LbfgsLogisticRegressionBinaryTrainer
- SdcaLogisticRegressionBinaryTrainer
- SdcaNonCalibratedBinaryTrainer
- SymbolicSgdLogisticRegressionBinaryTrainer
For the file classification application, we will be utilizing the SDCALogisticRegressionBinaryTrainer model.
