The Strategic Use of Sequential Feature Selector for Housing Price Predictions
To understand housing prices better, simplicity and clarity in our models are key. Our aim with this post is to demonstrate how straightforward yet powerful techniques in feature selection and engineering can lead to creating an effective, simple linear regression model. Working with the Ames dataset, we use a Sequential Feature Selector (SFS) to identify the most impactful numeric features and then enhance our model’s accuracy through thoughtful feature engineering.
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The Strategic Use of Sequential Feature Selector for Housing Price Predictions
Photo by Mahrous Houses.