A study on classification learning algorithms to predict crime status.
In the recent past, there has been a huge increase in the crime rate, hence the significance of task to predict, prevent or solve the crimes. In this paper, we conducted an experiment to obtain better supervised classification learning algorithms to predict crime status by using two different featur...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Advanced Institute of Convergence Information Technology
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/30681/ http://psasir.upm.edu.my/id/eprint/30681/1/A%20study%20on%20classification%20learning%20algorithms%20to%20predict%20crime%20status.pdf |
| _version_ | 1848846747497922560 |
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| author | Shojaee, Somayeh Mustapha, Aida Sidi, Fatimah A. Jabar, Marzanah |
| author_facet | Shojaee, Somayeh Mustapha, Aida Sidi, Fatimah A. Jabar, Marzanah |
| author_sort | Shojaee, Somayeh |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | In the recent past, there has been a huge increase in the crime rate, hence the significance of task to predict, prevent or solve the crimes. In this paper, we conducted an experiment to obtain better supervised classification learning algorithms to predict crime status by using two different feature selection methods tested on real dataset. Comparisons in terms of Area Under Curve (AUC), that
Naïve Bayesian (0.898), k-Nearest Neighbor (k-NN) (0.895) and Neural Networks (MultilayerPerceptron) (0.892) are better classifiers against Decision Tree (J48) (0.727), and Support Vector Machine (SVM) (0.678). Furthermore, the performance of mining results is improved by using
Chi-square feature selection technique. |
| first_indexed | 2025-11-15T09:07:37Z |
| format | Article |
| id | upm-30681 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T09:07:37Z |
| publishDate | 2013 |
| publisher | Advanced Institute of Convergence Information Technology |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-306812016-01-28T07:45:12Z http://psasir.upm.edu.my/id/eprint/30681/ A study on classification learning algorithms to predict crime status. Shojaee, Somayeh Mustapha, Aida Sidi, Fatimah A. Jabar, Marzanah In the recent past, there has been a huge increase in the crime rate, hence the significance of task to predict, prevent or solve the crimes. In this paper, we conducted an experiment to obtain better supervised classification learning algorithms to predict crime status by using two different feature selection methods tested on real dataset. Comparisons in terms of Area Under Curve (AUC), that Naïve Bayesian (0.898), k-Nearest Neighbor (k-NN) (0.895) and Neural Networks (MultilayerPerceptron) (0.892) are better classifiers against Decision Tree (J48) (0.727), and Support Vector Machine (SVM) (0.678). Furthermore, the performance of mining results is improved by using Chi-square feature selection technique. Advanced Institute of Convergence Information Technology 2013-05 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30681/1/A%20study%20on%20classification%20learning%20algorithms%20to%20predict%20crime%20status.pdf Shojaee, Somayeh and Mustapha, Aida and Sidi, Fatimah and A. Jabar, Marzanah (2013) A study on classification learning algorithms to predict crime status. International Journal of Digital Content Technology and its Applications, 7 (9). pp. 361-369. ISSN 1975-9339 English |
| spellingShingle | Shojaee, Somayeh Mustapha, Aida Sidi, Fatimah A. Jabar, Marzanah A study on classification learning algorithms to predict crime status. |
| title | A study on classification learning algorithms to predict crime status. |
| title_full | A study on classification learning algorithms to predict crime status. |
| title_fullStr | A study on classification learning algorithms to predict crime status. |
| title_full_unstemmed | A study on classification learning algorithms to predict crime status. |
| title_short | A study on classification learning algorithms to predict crime status. |
| title_sort | study on classification learning algorithms to predict crime status. |
| url | http://psasir.upm.edu.my/id/eprint/30681/ http://psasir.upm.edu.my/id/eprint/30681/1/A%20study%20on%20classification%20learning%20algorithms%20to%20predict%20crime%20status.pdf |