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.
Swipe to start coding
Your task is to create a model to solve the regression task on the diabetes dataset:
- Use a simple Linear Regression model as the base model of an ensemble.
- Create an AdaBoost Regressor model with the 50 base estimators.
- Print MSE to estimate regression quality.
Oplossing
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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.
Swipe to start coding
Your task is to create a model to solve the regression task on the diabetes dataset:
- Use a simple Linear Regression model as the base model of an ensemble.
- Create an AdaBoost Regressor model with the 50 base estimators.
- Print MSE to estimate regression quality.
Oplossing
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