Histogram Plots of StandardScaler Transformed Input Variables for the Sonar Dataset

How to Use StandardScaler and MinMaxScaler Transforms in Python

Many machine learning algorithms perform better when numerical input variables are scaled to a standard range. This includes algorithms that use a weighted sum of the input, like linear regression, and algorithms that use distance measures, like k-nearest neighbors. The two most popular techniques for scaling numerical data prior to modeling are normalization and standardization. […]

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Bar Chart of the Input Features (x) vs. the Mutual Information Feature Importance (y)

How to Perform Feature Selection With Numerical Input Data

Feature selection is the process of identifying and selecting a subset of input features that are most relevant to the target variable. Feature selection is often straightforward when working with real-valued input and output data, such as using the Pearson’s correlation coefficient, but can be challenging when working with numerical input data and a categorical […]

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