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Please enable JavaScript in your browser settings or update your browser.Challenge: Solving Task Using AdaBoost Regressor | Commonly Used Boosting Models
Ensemble Learning
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Conteúdo do Curso

Ensemble Learning

Ensemble Learning

1. Basic Principles of Building Ensemble Models
What is Ensemble of Models?Bagging ModelsBoosting ModelsStacking Models
2. Commonly Used Bagging Models
Bagging ClassifierChallenge: Solving Task Using Bagging ClassifierBagging RegressorChallenge: Solving Task Using Bagging RegressorRandom ForestChallenge: Determining Feature Importances Using Random ForestExtraTrees
3. Commonly Used Boosting Models
AdaBoost ClassifierChallenge: Solving Task Using AdaBoost ClassifierChallenge: Solving Task Using AdaBoost RegressorGradient BoostingXGBoostChallenge: Solving Task Using XGBoost
4. Commonly Used Stacking Models
Stacking ClassifierChallenge: Solving Task Using Stacking ClassifierChallenge: Solving Task Using Stacking RegressorUsing Ensembles As Base ModelsCourse Summary

bookChallenge: 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.

Tarefa

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.

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Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 3. Capítulo 3
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bookChallenge: 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.

Tarefa

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.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 3. Capítulo 3
toggle bottom row

bookChallenge: 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.

Tarefa

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.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

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.

Tarefa

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.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 3. Capítulo 3
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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