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It is definitely possible using the low-level API: some linear models can be 'incrementally trained' using 'initial predictor' to initialize themselves. In #653 there is a code sample (look for TrainWithInitialPredictor test).
We are working on making a high-level API that would support such a scenario: see #584 for the list of things we want to enable.
For instance, this is how currently (in my local branch) I perform incremental training:
// Pipeline.varpipeline=newMyTextLoader(env,MakeSentimentTextLoaderArgs()).Append(newMyTextTransform(env,MakeSentimentTextTransformArgs()));// Train the pipeline, prepare train set.varreader=pipeline.Fit(newMultiFileSource(dataPath));vartrainData=reader.Read(newMultiFileSource(dataPath));// Train the first predictor.vartrainer=newMySdca(env,newLinearClassificationTrainer.Arguments{NumThreads=1},"Features","Label");varfirstPredictor=trainer.Fit(trainData);// Train the second predictor on the same data.varsecondTrainer=newMyAveragedPerceptron(env,newAveragedPerceptronTrainer.Arguments(),"Features","Label");varfinalPredictor=secondTrainer.Train(trainData,firstPredictor.InnerModel);
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Zruty0 commentedon Aug 14, 2018
It is definitely possible using the low-level API: some linear models can be 'incrementally trained' using 'initial predictor' to initialize themselves. In #653 there is a code sample (look for
TrainWithInitialPredictor
test).We are working on making a high-level API that would support such a scenario: see #584 for the list of things we want to enable.
For instance, this is how currently (in my local branch) I perform incremental training:
MaxAkbar commentedon Aug 15, 2018
Thank you this is very helpful 👍 will take a look.