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  1. Impact of Scaling on Feature Selection with RFE

    Impact of Scaling on Feature Elimination with RFE

    In this project, we will investigate how scaling the data impacts the output of a number of feature selection tools in scikit-learn.

    In particular we will look into

    • Linear Regression
    • Decisition Tree Regression
    • Support Vector Regression

    For this project we will use the Auto MPG data set. Please follow the instructions in the post Working with the Auto MPG Data Set read more

  2. Impact of Scaling on Machine Learning Regression Algorithms

    Impact of Scaling on Machine Learning Regression Algorithms

    In this project, we will investigate how scaling the data impacts the performance of a variety of machine learning algorithms for prediction.

    In particular we will look into

    • Linear Regression and other linear models
    • K-nearest Regression
    • Decisition Tree Regression
    • Support Vector Regression
    • Bagging algorithms
    • Boosting algorithms

    For this project we will use the Auto MPG read more

  3. Working with the Auto MPG Data Set

    Working with the Auto MPG Data Set

    In this post we will look into the Auto MPG data set and clean it so that it is ready for further use.

    This data set shows the mpg of a group of car models produced in the 1970s and the 1980s along with some characteristic information associated with each model. More information about the data set can be found here read more

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