An Empirical Analysis of Machine Learning Algorithms for Crime Prediction Using Stacked Generalization: An Ensemble Approach
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G. R. Sinha | Surbhi Bhatia | Mohammad Tabrez Quasim | Bhavana Narain | Sapna Singh Kshatri | Deepak Singh | G. Sinha | Surbhi Bhatia | Bhavana Narain | Deepak Singh | M. Quasim
[1] G. R. Sinha,et al. Research studies on human cognitive ability , 2018, Int. J. Intell. Def. Support Syst..
[2] P. Venkata Krishna,et al. Applicability of Rough Set Technique for Data Investigation and Optimization of Intrusion Detection System , 2013, QSHINE.
[3] Luiz G A Alves,et al. Crime prediction through urban metrics and statistical learning , 2017, Physica A: Statistical Mechanics and its Applications.
[4] Mehmed M. Kantardzic,et al. Cracking the Smart ClickBot , 2011, 2011 13th IEEE International Symposium on Web Systems Evolution (WSE).
[5] Haralambos Mouratidis,et al. Information Systems Security Criticality and Assurance Evaluation , 2010, AST/UCMA/ISA/ACN.
[6] Sunil Yadav,et al. Crime pattern detection, analysis & prediction , 2017, 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA).
[7] Md Nasir Sulaiman,et al. Improved method of classification algorithms for crime prediction , 2014, 2014 International Symposium on Biometrics and Security Technologies (ISBAST).
[8] Gordon F. Mulligan,et al. Using Geographically Weighted Regression to Explore Local Crime Patterns , 2007 .
[9] Sergey V. Ivanov,et al. Crime rate prediction in the urban environment using social factors , 2018 .
[10] Yonghong Peng,et al. Text mining for traditional Chinese medical knowledge discovery: A survey , 2010, J. Biomed. Informatics.
[11] Holly N. Dentz,et al. The impact of new vaccine introduction on immunization and health systems: a review of the published literature. , 2012, Vaccine.
[12] V. Borooah. Deprivation, Violence, and Conflict: An Analysis of Naxalite Activity in the Districts of India , 2008 .
[13] Abdulaziz Almehmadi,et al. Language usage on Twitter predicts crime rates , 2017, SIN.
[14] Mark van der Laan,et al. Use of a machine learning framework to predict substance use disorder treatment success , 2017, PloS one.
[15] Muhammad Lawan Jibril,et al. Predictive Supervised Machine Learning Models for Diabetes Mellitus , 2020, SN Comput. Sci..
[16] Nor Azizah Ali,et al. An overview on crime prediction methods , 2017, 2017 6th ICT International Student Project Conference (ICT-ISPC).
[17] Jane Labadin,et al. Predicting Petroleum Reservoir Properties from Downhole Sensor Data using an Ensemble Model of Neural Networks , 2013, MLSDA '13.
[18] Hans-Christian Hege,et al. amira: A Highly Interactive System for Visual Data Analysis , 2005, The Visualization Handbook.
[19] Emma Vere-Jones,et al. The impact of the new , 2007 .
[20] Masoumeh Zareapoor,et al. Analysis of Credit Card Fraud Detection Techniques: based on Certain Design Criteria , 2012 .
[21] David H. Wolpert,et al. Stacked generalization , 1992, Neural Networks.
[22] Fitriana Harahap,et al. Implementation of Naïve Bayes Classification Method for Predicting Purchase , 2018, 2018 6th International Conference on Cyber and IT Service Management (CITSM).
[23] ABHISHEK MISAL,et al. DENOISING OF PCG SIGNAL BY USING WAVELET TRANSFORMS , 2012 .
[24] U. Rajendra Acharya,et al. Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring , 2019, Appl. Soft Comput..
[25] Binxu Zhai,et al. Development of a stacked ensemble model for forecasting and analyzing daily average PM2.5 concentrations in Beijing, China. , 2018, The Science of the total environment.
[26] Leslie W. Kennedy,et al. Risk Terrain Modeling: Brokering Criminological Theory and GIS Methods for Crime Forecasting , 2011 .
[27] Yao Hu,et al. Towards modeling of resilience dynamics in manufacturing enterprises: Literature review and problem formulation , 2008, 2008 IEEE International Conference on Automation Science and Engineering.
[28] Elli Angelopoulou,et al. The Random Forest Classifier in WEKA: Discussion and New Developments for Imbalanced Data , 2018, 1812.08102.
[29] Zhiang Wu,et al. Spatio-Temporal Pattern Analysis and Prediction for Urban Crime , 2018, 2018 Sixth International Conference on Advanced Cloud and Big Data (CBD).
[30] P. Venkata Krishna,et al. Analyzing Intrusion Detection System: An ensemble based stacking approach , 2014, 2014 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT).
[31] Jane Labadin,et al. Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization , 2015 .
[32] Mohammad Reza Parsaei,et al. A Hybrid Data Mining Approach for Intrusion Detection on Imbalanced NSL-KDD Dataset , 2016 .
[33] Jane Labadin,et al. Applied Soft Computing , 2014 .
[34] Jane Labadin,et al. Ensemble model of Artificial Neural Networks with randomized number of hidden neurons , 2013, 2013 8th International Conference on Information Technology in Asia (CITA).
[35] Jane Labadin,et al. Ensemble Learning Model for Petroleum Reservoir Characterization: A Case of Feed-Forward Back-Propagation Neural Networks , 2013, PAKDD Workshops.