在印度各邦使用基于规则的决策树J48分类算法预测针对妇女的犯罪行为

S. Lavanya, D. Akila
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引用次数: 1

摘要

对妇女的犯罪除了经济文明的发展之外,还处于集体社会生命周期的困境之中。通过扩大违规行为,规则实施组织继续朝着请求驱动框架和新方法发展,以改善不法行为调查并更好地确保其网络安全。基于规则的决策树(RBDT J48)和朴素贝叶斯算法的功能发生框架的命令实现和智能调查包含改进问题的能力。信息挖掘方法站在引文信息可得的方向上,频繁出现巨大的记录集;最广泛的机器学习征集消费准备了这一重要的探索领域。犯罪类型对违法个体的分类具有递进倾向。探索利用基于规则的决策树(RBDT J48)计算和朴素贝叶斯测量了错误预期模型的改进,因为它被认为是预测错误信息的最有效的人工智能计算。进一步考虑两种不同的分组计算,朴素贝叶斯和基于规则的决策树J48,用于预测印度各邦的不法行为类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction Performance of Crime Against Women Using Rule Based Decision Tree J48 Classification Algorithms in various states of India
Crimes against women be situated collective societal difficult distressing eminence of lifecycle in addition monetary development of a civilization. Through expanding violations, rule implementations organizations remain proceeding towards request propelled frameworks and new ways to deal with improving wrongdoing investigation and better ensure their networks. Rule Based Decision tree (RBDT J48) and Naive Bayesian algorithm functional happening framework of commandment implementation then cleverness investigation embraces capacity of improving problems. Information Mining stands method in the direction of citation information available, frequently huge record sets; the widest collection of machine learning solicitations consumes prepared this one significant field of exploration. Crime type stands progression intentions towards classify law-breaking individualities. Exploration measured improvement in wrongdoing expectation model utilizing Rule Based Decision Tree (RBDT J48) calculation and Naive bayes since it has been considered as the most effective AI calculation for a forecast of wrongdoing information. And furthermore think about the two distinctive grouping calculations to be specific, Naive bayes and Rule Based Decision Tree J48 for anticipating wrongdoing type for various states in India.
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