An Empirical Analysis of Machine Learning Algorithms for Crime Prediction Using Stacked Generalization: An Ensemble Approach

An Empirical Analysis of Machine Learning Algorithms for Crime Prediction Using Stacked Generalization: An Ensemble Approach

Ensemble learning method is a collaborative decision-making mechanism that implements to aggregate the predictions of learned classifiers in order to produce new instances. Early analysis has shown that the ensemble classifiers are more reliable than any single part classifier, both empirically and...

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Bibliographic Details
Main Authors: Sapna Singh Kshatri, Deepak Singh, Bhavana Narain, Surbhi Bhatia, Mohammad Tabrez Quasim, G. R. Sinha
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Boosting classifier
ensemble classifiers
Indian crime prediction
machine learning
statistical classifiers
stacking
Online Access:https://ieeexplore.ieee.org/document/9410543/

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