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The present chapter discusses various types of activation functionsActivation function, Artificial NeuralNetwork NetworksArtificial Neural Networks (ANN), Wavelet Neural NetworksWavelet Neural Networks (WNN), Support Vector RegressionSupport Vector Regression (SVR), Extreme Learning Machine, Logistic RegressionLogistic Regression (LR), and K-Nearest NeighbourK-Nearest Neighbour (KNN) are part of the chapter. Each algorithm is explained with detailed mathematical philosophy and governing parametersParameters. A number of well-thought-out numerical problems and references were provided to help the reader understand the material effectively. In summary, the reader is expected to get insights about classical algorithmsAlgorithms, which are prerequisites to understanding, before proceeding further to advanced algorithms.

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Classical Machine Learning Algorithms

  • 章节

  • 发表日期：

    2025年

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  • Komaragiri Srinivasa Raju,
  • Dasika Nagesh Kumar

摘要

The present chapter discusses various types of activation functionsActivation function, Artificial NeuralNetwork NetworksArtificial Neural Networks (ANN), Wavelet Neural NetworksWavelet Neural Networks (WNN), Support Vector RegressionSupport Vector Regression (SVR), Extreme Learning Machine, Logistic RegressionLogistic Regression (LR), and K-Nearest NeighbourK-Nearest Neighbour (KNN) are part of the chapter. Each algorithm is explained with detailed mathematical philosophy and governing parametersParameters. A number of well-thought-out numerical problems and references were provided to help the reader understand the material effectively. In summary, the reader is expected to get insights about classical algorithmsAlgorithms, which are prerequisites to understanding, before proceeding further to advanced algorithms.