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Lære Challenge: Solving Task Using AdaBoost Regressor | Commonly Used Boosting Models
Ensemble Learning
course content

Kursusindhold

Ensemble Learning

Ensemble Learning

1. Basic Principles of Building Ensemble Models
2. Commonly Used Bagging Models
3. Commonly Used Boosting Models
4. Commonly Used Stacking Models

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Challenge: Solving Task Using AdaBoost Regressor

AdaBoost Regressor is an ensemble learning algorithm used for regression tasks.

The principle of work of such a regressor coincides with the principle of work of the AdaBoost Classifier. The only difference is that we use some regression algorithms (linear regression, decision tree regressor, polynomial regression, etc.) as a base model.

The AdaBoostRegressor class in Python provides tools to train the model and make predictions.

Opgave

Swipe to start coding

Your task is to create a model to solve the regression task on the diabetes dataset:

  1. Use a simple Linear Regression model as the base model of an ensemble.
  2. Create an AdaBoost Regressor model with the 50 base estimators.
  3. Print MSE to estimate regression quality.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 3. Kapitel 3
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book
Challenge: Solving Task Using AdaBoost Regressor

AdaBoost Regressor is an ensemble learning algorithm used for regression tasks.

The principle of work of such a regressor coincides with the principle of work of the AdaBoost Classifier. The only difference is that we use some regression algorithms (linear regression, decision tree regressor, polynomial regression, etc.) as a base model.

The AdaBoostRegressor class in Python provides tools to train the model and make predictions.

Opgave

Swipe to start coding

Your task is to create a model to solve the regression task on the diabetes dataset:

  1. Use a simple Linear Regression model as the base model of an ensemble.
  2. Create an AdaBoost Regressor model with the 50 base estimators.
  3. Print MSE to estimate regression quality.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 3. Kapitel 3
Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
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