机器学习
计算机科学
决策树
人工智能
混淆矩阵
算法
Python(编程语言)
支持向量机
混乱
统计分类
数据挖掘
心理学
精神分析
操作系统
作者
Bilal Abdualgalil,Sajimon Abraham
出处
期刊:2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE)
日期:2020-02-01
卷期号:: 1-6
被引量:26
标识
DOI:10.1109/ic-etite47903.2020.490
摘要
Machine learning algorithms are mostly used in data classification and regression. This paper is a review of Machine learning algorithms such as Decision Tree, SVM, KNN, NB, and RF. This work compares the performance of these algorithms to find accuracy, confusion matrix, training, and prediction time. This work uses the dataset consisting of 786 instances and 8 attributes that are preprocessed and labeled using Python software.
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