Search results for "normalize"

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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Singular Value Decomposition for Dimensionality Reduction in Python

Singular Value Decomposition for Dimensionality Reduction in Python

Reducing the number of input variables for a predictive model is referred to as dimensionality reduction. Fewer input variables can result in a simpler predictive model that may have better performance when making predictions on new data. Perhaps the more popular technique for dimensionality reduction in machine learning is Singular Value Decomposition, or SVD for […]

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Box Plot of PCA Number of Components vs. Classification Accuracy

Principal Component Analysis for Dimensionality Reduction in Python

Reducing the number of input variables for a predictive model is referred to as dimensionality reduction. Fewer input variables can result in a simpler predictive model that may have better performance when making predictions on new data. Perhaps the most popular technique for dimensionality reduction in machine learning is Principal Component Analysis, or PCA for […]

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A Gentle Introduction to Dimensionality Reduction for Machine Learning

Introduction to Dimensionality Reduction for Machine Learning

The number of input variables or features for a dataset is referred to as its dimensionality. Dimensionality reduction refers to techniques that reduce the number of input variables in a dataset. More input features often make a predictive modeling task more challenging to model, more generally referred to as the curse of dimensionality. High-dimensionality statistics […]

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Distance Measures for Machine Learning

4 Distance Measures for Machine Learning

Distance measures play an important role in machine learning. They provide the foundation for many popular and effective machine learning algorithms like k-nearest neighbors for supervised learning and k-means clustering for unsupervised learning. Different distance measures must be chosen and used depending on the types of the data. As such, it is important to know […]

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