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feat: Adding AdaBoost Classification #402

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Added AdaBoost Classification with FlAML framework.

Testing

Choosing dataset and Classification ML workflow

Select data:
d66255f84c9bfce4410cdbcbf4c6c186

Here we select column 2 "Label" for Y set, column [3,12] as X set.
9fa29828e8490f6a1f8c1ce66220e025

Then choose mode2: Classification. Here we can see "AdaBoost" in label 11:
9de4f361e67ae3c786edade1b95eed9e

In feature engineering part we get the data.
4349bd32d6a2fefa531a7fe5b63628d1

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.

4477471d0b6bd9f34de78579ba3cc823

Training and collecting result:

b9b146441a0ed6e5711e757fc5d7c7de

d8881aee06faa8221cfa89a4c98b28fe

AutoML Workflow

Select AutoML here:
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Auto tuning:
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Final Result:
392a86a04e416eed135a71c83a1089d5

@HaibinLai
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Choosing dataset and Classification ML workflow

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AdaBoost in non-autoML workflow

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AutoML
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final Result
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@HaibinLai HaibinLai closed this Jan 19, 2025
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