Trainers in ML.NET

Machine learning tasks like regression and classification contain various algorithm implementations. 

Some tasks may utilize the same algorithm, such as the SDCA algorithm in both Binary Classification and Regression tasks

 

In some cases, the problem you are trying to solve and the way your data is structured does not fit well into the current algorithm.

If so, consider using a different algorithm for your task to see if it learns better from your data.

 

A trainer identifies a single algorithm used for a single task (i.e. Trainer = Algorithm + Task).

Listed below is a summary of trainers available in ML.NET. For more info, see guidance on which algorithm to choose.

 

Trainer	Algorithm	Task	ONNX Exportable
SdcaLogisticRegressionBinaryTrainer	SDCA	Binary classification	Yes
SdcaNonCalibratedBinaryTrainer	SDCA	Binary classification	Yes
SdcaMaximumEntropyMulticlassTrainer	SDCA	Multiclass classification	Yes
SdcaNonCalibratedMulticlassTrainer	SDCA	Multiclass classification	Yes
SdcaRegressionTrainer	SDCA	Regression	Yes
AveragedPerceptronTrainer	Averaged Perceptron	Binary classification	Yes
LbfgsLogisticRegressionBinaryTrainer	L-BFGS	Binary classification	Yes
LbfgsMaximumEntropyMulticlassTrainer	L-BFGS	Multiclass classification	Yes
LbfgsPoissonRegressionTrainer	L-BFGS	Regression	Yes
SymbolicSgdLogisticRegressionBinaryTrainer	Symbolic stochastic gradient descent	Binary classification	Yes
OnlineGradientDescentTrainer	Online gradient descent	Regression	Yes
LightGbmBinaryTrainer	Light gradient boosted machine	Binary classification	Yes
LightGbmMulticlassTrainer	Light gradient boosted machine	Multiclass classification	Yes
LightGbmRegressionTrainer	Light gradient boosted machine	Regression	Yes
LightGbmRankingTrainer	Light gradient boosted machine	Ranking	No
FastTreeBinaryTrainer	Fast Tree	Binary classification	Yes
FastTreeRegressionTrainer	Fast Tree	Regression	Yes
FastTreeTweedieTrainer	Fast Tree	Regression	Yes
FastTreeRankingTrainer	Fast Tree	Ranking	No
FastForestBinaryTrainer	Fast Forest	Binary classification	Yes
FastForestRegressionTrainer	Fast Forest	Regression	Yes
GamBinaryTrainer	Generalized additive model	Binary classification	No
GamRegressionTrainer	Generalized Additive Model	Regression	No
MatrixFactorizationTrainer	Matrix Factorization	Recommendation	No
FieldAwareFactorizationMachineTrainer	Field Aware Factorization Machine	Binary classification	No
OneVersusAllTrainer	One Versus All	Multiclass classification	Yes
PairwiseCouplingTrainer	Pairwise Coupling	Multiclass classification	No
KMeansTrainer	KMeans	Clustering	Yes
RandomizedPcaTrainer	Randomized Pca	Anomaly detection	No
NaiveBayesMulticlassTrainer	Naive Bayes Multiclass	Multiclass classification	Yes
PriorTrainer	Prior	Binary classification	Yes
LinearSvmTrainer	Linear Svm	Binary classification	Yes
LdSvmTrainer	Ld Svm	Binary classification	Yes
OlsTrainer	Ols	Regression	Yes