犯罪率的离散化从数字到分类

S. Memon, F. Akhtar, A. Nazir, Ahsan Wajahat, Sirajuddin Qureshi, Faheem Ullah, A. Shakeel
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引用次数: 1

摘要

本研究的目的是将犯罪率数据离散为分类值,并找出多个城市不同犯罪率之间的关联。回归模型用于在所有其他或某些其他犯罪率的基础上回归一个犯罪率的值。根据美国的犯罪统计数据,本研究的重点是识别美国多个城市的可变犯罪,并应用机器学习技术对犯罪数据进行分类,建立数据离散化和预处理过程。
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Discretization of the Crime Rate from Numerical Into Categorical
The objective of this study is to discretize the crime rate figures into categorical values and to find associations between different crime rates in multiple cities. Regression modeling is used to regress the value of one crime rate on the basis of all others or some of the other crimes rates. As per US statistics on crime, this research focused on identifying the variable crime in multiple cities of the US and categorized the data of crime by applying machine learning techniques with the establishment of data discretization and preprocessing process.
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