Challenge: Predicting Research Outcomes
In research, predicting outcomes based on multiple variables is a common task. Linear regression is a widely used method for modeling the relationship between one or more features and a continuous outcome. By using the scikit-learn library, you can efficiently fit a regression model, extract its coefficients, and evaluate its performance with the R^2 score. This challenge provides you with a DataFrame containing feature1, feature2, and outcome columns. Your goal is to fit a linear regression model using both features to predict the outcome, return the model's coefficients and R^2 score, and print a brief interpretation of the results.
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Given a DataFrame with columns 'feature1', 'feature2', and 'outcome', fit a linear regression model using both features to predict 'outcome'. Return the model's coefficients and R² score, and print a brief interpretation of the results.
- Select 'feature1' and 'feature2' as input features and 'outcome' as the target.
- Fit a linear regression model using the selected features.
- Obtain the coefficients of the fitted model.
- Compute the R² score of the model.
- Print an interpretation including the coefficients and R² score.
- Return the coefficients and R² score.
Рішення
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Can you show me how to fit the linear regression model using scikit-learn?
What do the coefficients and R^2 score mean in this context?
Can you provide an example interpretation of the results?
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In research, predicting outcomes based on multiple variables is a common task. Linear regression is a widely used method for modeling the relationship between one or more features and a continuous outcome. By using the scikit-learn library, you can efficiently fit a regression model, extract its coefficients, and evaluate its performance with the R^2 score. This challenge provides you with a DataFrame containing feature1, feature2, and outcome columns. Your goal is to fit a linear regression model using both features to predict the outcome, return the model's coefficients and R^2 score, and print a brief interpretation of the results.
Swipe to start coding
Given a DataFrame with columns 'feature1', 'feature2', and 'outcome', fit a linear regression model using both features to predict 'outcome'. Return the model's coefficients and R² score, and print a brief interpretation of the results.
- Select 'feature1' and 'feature2' as input features and 'outcome' as the target.
- Fit a linear regression model using the selected features.
- Obtain the coefficients of the fitted model.
- Compute the R² score of the model.
- Print an interpretation including the coefficients and R² score.
- Return the coefficients and R² score.
Рішення
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