Research Approach With Machine Learning Underpinned

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Abstract

This chapter describes several methodologies and proposed models used to examine the accuracy and efficiency of high-performance colon-cancer feature selection and classification algorithms to solve the problems identified in Chapter 2. An elaboration of the diverse methods of gene/feature selection algorithms and the related classification algorithms implemented throughout this study are presented. A prototypical methodology blueprint for each experiment is developed to answer the research questions in Chapter 1. Each system model is also presented, and the measures used to validate the performance of the model's outcome are discussed.
基于机器学习的研究方法
本章描述了几种方法和提出的模型,用于检查高性能结肠癌特征选择和分类算法的准确性和效率,以解决第2章中确定的问题。阐述了基因/特征选择算法的不同方法以及在本研究中实施的相关分类算法。每个实验的原型方法蓝图被开发来回答第1章中的研究问题。还介绍了每个系统模型,并讨论了用于验证模型结果性能的度量。
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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