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An Approach Towards Development of a Predictive Model for Female Kidnapping in India Using R Programming

机译:一种利用R编程发展印度女性绑架预测模型的途径

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The major concern of the present world is the increase in criminal activities that are taking place throughout the world. The criminal activities in today's world include murder, theft, rape, women exploitation, human trafficking, possession of illegal properties, kidnapping. This paper summarizes the criminal activities related to female kidnapping in India. This paper highlights the statistical analysis of female kidnapping in India and thereby develops a predictive model to envisage the purpose of kidnapping of an individual female based on certain parameters. The model is developed using the decision tree technique by applying Iterative Dichotomizer (ID3) algorithm. The ID3 algorithm uses the entropy measure as a criterion for selecting classifiers for branching. The raw data set is converted to an appropriate one by converting the categorical values to numerical values using label and one hot encoding. This model is then trained with the appropriate training data set, and then, its performance is evaluated with a testing data set. The efficiency of the model is detected with the measures of accuracy, precision, recall, Fl, AUC scores.
机译:本世界的主要问题是在全世界正在进行的犯罪活动增加。当今世界的犯罪活动包括谋杀,盗窃,强奸,妇女剥削,人口贩运,拥有非法性质,绑架。本文总结了与印度女性绑架有关的犯罪活动。本文突出了印度女性绑架的统计分析,从而制定了预测模型,以设想基于某些参数绑架单个女性的目的。该模型是通过应用迭代二甲甲醚(ID3)算法的决策树技术开发的。 ID3算法使用熵测量作为选择分支的分类器的标准。通过使用标签和一个热编码将分类值转换为数值来将原始数据集转换为适当的数据集。然后,此模型接受了适当的训练数据集,然后通过测试数据集进行评估其性能。通过精度,精度,召回,FL,AUC得分的测量来检测模型的效率。

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