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Paper Title

Classification, Prediction and Forecasting crime against women using machine learning algorithms

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Registration ID: IJNRD_194468

Published ID: IJNRD2305520

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Keywords

Classification, Prediction, Forecasting, Women,

Abstract

These days, crime against women has spread to every country in the world, and many are making efforts to stop it. To decrease the rising number of occurrences of crime against women, preventative steps are done. Every year, a vast amount of data is produced based on the reporting of crimes. This information may be highly helpful in analysing and forecasting crime and may even help us to some part prevent it. Crime analysis is a crucial area for the police force. Studying crime statistics can aid in the analysis of crime trends, interconnected hints, and significant hidden relationships between the crimes. Because of this, data mining may greatly aid in the analysis, visualization, and prediction of crime using crime data sets from various Indian states. A predetermined criteria is used to categorize the dataset. Here, the categorization is done in accordance with the numerous categories of crimes against women that are committed in various Indian states and cities. The administration might develop measures to prevent crimes against women and take effective action to reduce crime with the use of crime prediction. The supervised machine learning algorithm Random Forest Algorithm, which is very well-liked and utilized for Classification and Regression problems in Machine Learning, will be employed in the project. A forest is made up of many different types of trees, and the more trees there are, the more robust the forest will be.

How To Cite (APA)

Tanya Singh, Namya H S, Suchanda Dutta, Tirumala Reddy, & Dr. Manimozhi I (May-2023). Classification, Prediction and Forecasting crime against women using machine learning algorithms. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), f47-f50. https://ijnrd.org/papers/IJNRD2305520.pdf

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Paper Reg. ID: IJNRD_194468

Published Paper Id: IJNRD2305520

Research Area: Computer Science & Technologyร‚ย 

Author Type: Indian Author

Country: Bangalore, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305520.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305520

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