@Article{crph1334,
AUTHOR = {Gupta, Anuj Kumar and Buddula, Dheeraj Varun Kumar Reddy and Patchipulusu, Hari Hara Sudheer and Polu, Achuthananda Reddy and Narra, Bhumeka and Vattikonda, Navya},
TITLE = {An Analysis of Crime Prediction and Classification Using Data Mining Techniques},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2021},
NUMBER = {1},
PAGES = {156-166},
URL = {https://www.scipublications.com/journal/index.php/JAIBD/article/view/1334},
ISSN = {2831-5162},
DOI = {10.31586/jaibd.2021.1334},
ABSTRACT = {Crime is a serious and widespread problem in their society, thus preventing it is essential. Assignment. A significant number of crimes are committed every day. One tool for dealing with model crime is data mining. Crimes are costly to society in many ways, and they are also a major source of frustration for its members. A major area of machine learning research is crime detection. This paper analyzes crime prediction and classification using data mining techniques on a crime dataset spanning 2006 to 2016. This approach begins with cleaning and extracting features from raw data for data preparation. Then, machine learning and deep learning models, including RNN-LSTM, ARIMA, and Linear Regression, are applied. The performance of these models is evaluated using metrics like Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The RNN-LSTM model achieved the lowest RMSE of 18.42, demonstrating superior predictive accuracy among the evaluated models. Data visualization techniques further unveiled crime patterns, offering actionable insights to prevent crime.},
}

%0 Journal Article
%A Gupta, Anuj Kumar
%A Buddula, Dheeraj Varun Kumar Reddy
%A Patchipulusu, Hari Hara Sudheer
%A Polu, Achuthananda Reddy
%A Narra, Bhumeka
%A Vattikonda, Navya
%D 2021
%J Current Research in Public Health

%@ 2831-5162
%V 1
%N 1
%P 156-166

%T An Analysis of Crime Prediction and Classification Using Data Mining Techniques
%M doi:10.31586/jaibd.2021.1334
%U https://www.scipublications.com/journal/index.php/JAIBD/article/view/1334

TY  - JOUR
AU  - Gupta, Anuj Kumar
AU  - Buddula, Dheeraj Varun Kumar Reddy
AU  - Patchipulusu, Hari Hara Sudheer
AU  - Polu, Achuthananda Reddy
AU  - Narra, Bhumeka
AU  - Vattikonda, Navya
TI  - An Analysis of Crime Prediction and Classification Using Data Mining Techniques
T2  - Current Research in Public Health
PY  - 2021
VL  - 1
IS  - 1
SN  - 2831-5162
SP  - 156
EP  - 166
UR  - https://www.scipublications.com/journal/index.php/JAIBD/article/view/1334
AB  - Crime is a serious and widespread problem in their society, thus preventing it is essential. Assignment. A significant number of crimes are committed every day. One tool for dealing with model crime is data mining. Crimes are costly to society in many ways, and they are also a major source of frustration for its members. A major area of machine learning research is crime detection. This paper analyzes crime prediction and classification using data mining techniques on a crime dataset spanning 2006 to 2016. This approach begins with cleaning and extracting features from raw data for data preparation. Then, machine learning and deep learning models, including RNN-LSTM, ARIMA, and Linear Regression, are applied. The performance of these models is evaluated using metrics like Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The RNN-LSTM model achieved the lowest RMSE of 18.42, demonstrating superior predictive accuracy among the evaluated models. Data visualization techniques further unveiled crime patterns, offering actionable insights to prevent crime.
DO  - An Analysis of Crime Prediction and Classification Using Data Mining Techniques
TI  - 10.31586/jaibd.2021.1334
ER  -