SOCIO-ECONOMIC DETERMINANTS OF RECIDIVISM. SOME PROBLEMS OF IDENTIFICATION RELATIONSHIPS USING QUANTITATIVE METHODS

The aim of the author was to discuss an application of data mining and statistical methods to recidivism prediction. There was analysed a binary classification problem where the goal was to predict if a prisoner will be arrested for a certain type of crime within one year of being released from pris...

Full description

Bibliographic Details
Main Author: Kinga Kądziołka
Format: Article
Language:English
Published: University of Gdansk 2016-03-01
Series:Contemporary Economy
Subjects:
Online Access:http://www.wspolczesnagospodarka.pl/?p=1171
_version_ 1811264163498950656
author Kinga Kądziołka
author_facet Kinga Kądziołka
author_sort Kinga Kądziołka
collection DOAJ
description The aim of the author was to discuss an application of data mining and statistical methods to recidivism prediction. There was analysed a binary classification problem where the goal was to predict if a prisoner will be arrested for a certain type of crime within one year of being released from prison. There were compared different models such as neural network, classification tree, logistic regression and SVM. General accuracy of all the models exceeded 70% correctly classified instances, but all of the analysed classifiers were characterized by high “false negatives” ratio and so they would be useless in practice.
first_indexed 2024-04-12T19:58:13Z
format Article
id doaj.art-bbfef829f1d440f793da9095d5e95d7a
institution Directory Open Access Journal
issn 2082-677X
2082-677X
language English
last_indexed 2024-04-12T19:58:13Z
publishDate 2016-03-01
publisher University of Gdansk
record_format Article
series Contemporary Economy
spelling doaj.art-bbfef829f1d440f793da9095d5e95d7a2022-12-22T03:18:36ZengUniversity of GdanskContemporary Economy2082-677X2082-677X2016-03-01718194SOCIO-ECONOMIC DETERMINANTS OF RECIDIVISM. SOME PROBLEMS OF IDENTIFICATION RELATIONSHIPS USING QUANTITATIVE METHODSKinga Kądziołka0Prokuratura Okręgowa w KatowicachThe aim of the author was to discuss an application of data mining and statistical methods to recidivism prediction. There was analysed a binary classification problem where the goal was to predict if a prisoner will be arrested for a certain type of crime within one year of being released from prison. There were compared different models such as neural network, classification tree, logistic regression and SVM. General accuracy of all the models exceeded 70% correctly classified instances, but all of the analysed classifiers were characterized by high “false negatives” ratio and so they would be useless in practice.http://www.wspolczesnagospodarka.pl/?p=1171risk of recidivismsurvival analysislogistic regressiondata mining
spellingShingle Kinga Kądziołka
SOCIO-ECONOMIC DETERMINANTS OF RECIDIVISM. SOME PROBLEMS OF IDENTIFICATION RELATIONSHIPS USING QUANTITATIVE METHODS
Contemporary Economy
risk of recidivism
survival analysis
logistic regression
data mining
title SOCIO-ECONOMIC DETERMINANTS OF RECIDIVISM. SOME PROBLEMS OF IDENTIFICATION RELATIONSHIPS USING QUANTITATIVE METHODS
title_full SOCIO-ECONOMIC DETERMINANTS OF RECIDIVISM. SOME PROBLEMS OF IDENTIFICATION RELATIONSHIPS USING QUANTITATIVE METHODS
title_fullStr SOCIO-ECONOMIC DETERMINANTS OF RECIDIVISM. SOME PROBLEMS OF IDENTIFICATION RELATIONSHIPS USING QUANTITATIVE METHODS
title_full_unstemmed SOCIO-ECONOMIC DETERMINANTS OF RECIDIVISM. SOME PROBLEMS OF IDENTIFICATION RELATIONSHIPS USING QUANTITATIVE METHODS
title_short SOCIO-ECONOMIC DETERMINANTS OF RECIDIVISM. SOME PROBLEMS OF IDENTIFICATION RELATIONSHIPS USING QUANTITATIVE METHODS
title_sort socio economic determinants of recidivism some problems of identification relationships using quantitative methods
topic risk of recidivism
survival analysis
logistic regression
data mining
url http://www.wspolczesnagospodarka.pl/?p=1171
work_keys_str_mv AT kingakadziołka socioeconomicdeterminantsofrecidivismsomeproblemsofidentificationrelationshipsusingquantitativemethods