Mahout has an implementation of meta-learners of OnlineLogisticRegression, in which each learner is trained using different learning rates, this implementation is called AdaptiveLogisticRegression. By default, it trains 100 regression learners and tosses out learners with lower performance after separating learners that have different learning rates.

Let's look at how to execute AdaptiveLogisticRegression using the Mahout command line.

mahout trainAdaptiveLogistic --input train_data/input_bank_data.csv --output model --target y --predictors age job marital education default housing loan contact month day_of_week duration campaign pdays previous poutcome emp.var.rate cons.price.idx cons.conf.idx euribor3m nr.employed --types n w w w w w w w w w n n n n w n n n n n --features 20 --passes 100 --categories 2 --threads 20

To validate the model, we will use the validateAdaptiveLogistic command. Let's look at the arguments to the command:

mahout validateAdaptiveLogistic...