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Crime Analysis in India with Interactive Visualization

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Avani Vaishnav, Ayana Holla P., Aishwarya Vijaykumar Sheelvant

Avani Vaishnav, Ayana Holla P. and Aishwarya Vijaykumar Sheelvant. Crime Analysis in India with Interactive Visualization. International Journal of Computer Applications 183(26):31-38, September 2021. BibTeX

	author = {Avani Vaishnav and Ayana Holla P. and Aishwarya Vijaykumar Sheelvant},
	title = {Crime Analysis in India with Interactive Visualization},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2021},
	volume = {183},
	number = {26},
	month = {Sep},
	year = {2021},
	issn = {0975-8887},
	pages = {31-38},
	numpages = {8},
	url = {},
	doi = {10.5120/ijca2021921651},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Evaluating and predicting the crime rate in any country is critical for the concerned government authorities to find ways to minimize its effect on the community and to devise methods to ultimately curb such practices. Previous study suggests a correlation between education in a country and the rate of poverty, education, and unemployment as well as unemployment and poverty in the country. This paper tries to introduce a computational model to analyze the relationship between education, poverty and unemployment rates to the crime rates in each state of India as well as the rate of crime contribution to the total crime rate in each state. Data is sourced from verified and trusted government data collection websites to keep the study authentic. The paper uses Machine Learning to recognize the influence each of the chosen socio-economic indicators has on crime as a whole. This approach consists of three components: data collection and pre-processing, employing the proposed machine learning algorithms such as simple linear regression and multiple linear regression, and lastly, visualizing data.


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Ordinary Least Square, Visualization, Data Cleaning, Analysis of Crime Dataset, Regression.