机器学习估算器：Python 中的实现与比较

IF 1 4区数学 Q3 MATHEMATICS, APPLIED

Computational Methods in Applied Mathematics Pub Date : 2024-01-24 DOI:10.1515/cmam-2023-0198

Fabian Merle

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引用次数: 0

摘要

我们比较了不同的机器学习估计器，并详细介绍了它们在 Python 中的实现。我们针对分类和回归问题进行了计算研究。此外，作为机器学习的基础问题之一，我们介绍了手写数字识别的具体分类任务。在这方面，我们讨论了这个问题的数学表述，当然还有实现细节。所有相应的 Python 代码都会应要求提供，并可从作者的 GitHub 页面 https://github.com/Fab1Fatal 下载。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Machine Learning Estimators: Implementation and Comparison in Python

We compare different machine learning estimators and present details about their implementation in Python. The computational studies are conducted for classification as well as regression problems. Moreover, as one of the founding problems of machine learning, we present the specific classification task of handwritten digit recognition. In this connection, we discuss the mathematical formulation and of course the implementation details of this problem. All corresponding Python code is fully provided on request and can be downloaded from the author’s GitHub page https://github.com/Fab1Fatal.

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来源期刊

Computational Methods in Applied Mathematics MATHEMATICS, APPLIED-

CiteScore

2.40

自引率

7.70%

发文量

期刊介绍： The highly selective international mathematical journal Computational Methods in Applied Mathematics　(CMAM) considers original mathematical contributions to computational methods and numerical analysis with applications mainly related to PDEs. CMAM seeks to be interdisciplinary while retaining the common thread of numerical analysis, it is intended to be readily readable and meant for a wide circle of researchers in applied mathematics. The journal is published by De Gruyter on behalf of the Institute of Mathematics of the National Academy of Science of Belarus.