feat: Adding Adaboost Classification

[HaibinLai]

Added AdaBoost Classification with FlAML framework.

Testing

Choosing dataset and Classification ML workflow

Select data:

Here we select column 2 "Label" for Y set, column [3,12] as X set.

Then choose mode2: Classification. Here we can see "AdaBoost" in label 11:

In feature engineering part we get the data.

AdaBoost in non-autoML workflow

Select parameters for AdaBoost. Here we expose 3 hyperparameter in the model: N estimator for how many decision trees we are going to use, Learning rate for the model, max_depth for the depth of the decision trees used in AdaBoost.

Training and collecting result:

AutoML Workflow

Auto tuning:

Final Result: