Predictive data mining based on similarity and clustering methods.

Predictive data mining is an attractive goal in data mining. It has wide application, including credit evaluation, sales promotion, financial forecasting and market trend analysis. In this paper we propose a predictive data mining model based on the combination of similarity, clustering and predicti...

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Main Authors: Defit, Sarjon, Md. Sap, Mohd. Noor
Format: Article
Language:English
Published: Penerbit UTM Press 2000
Subjects:
Online Access:http://eprints.utm.my/8711/1/SarjonDefit2000_PredictiveDataMiningBasedOnSimilarity.pdf
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author Defit, Sarjon
Md. Sap, Mohd. Noor
author_facet Defit, Sarjon
Md. Sap, Mohd. Noor
author_sort Defit, Sarjon
collection ePrints
description Predictive data mining is an attractive goal in data mining. It has wide application, including credit evaluation, sales promotion, financial forecasting and market trend analysis. In this paper we propose a predictive data mining model based on the combination of similarity, clustering and predictive modeling. This model is implemented and tested using real estate data. Our study concludes that our predictive data mining model can improve the prediction ability by using all attributes in the different clusters with the nearest distance as input fields. In this paper we explain the importance of data mining, similarity, the proposed predictive data mining model, the testing of the model, discussion and conclusion.
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spelling utm.eprints-87112017-11-01T04:17:52Z http://eprints.utm.my/8711/ Predictive data mining based on similarity and clustering methods. Defit, Sarjon Md. Sap, Mohd. Noor QA75 Electronic computers. Computer science Predictive data mining is an attractive goal in data mining. It has wide application, including credit evaluation, sales promotion, financial forecasting and market trend analysis. In this paper we propose a predictive data mining model based on the combination of similarity, clustering and predictive modeling. This model is implemented and tested using real estate data. Our study concludes that our predictive data mining model can improve the prediction ability by using all attributes in the different clusters with the nearest distance as input fields. In this paper we explain the importance of data mining, similarity, the proposed predictive data mining model, the testing of the model, discussion and conclusion. Penerbit UTM Press 2000-12 Article PeerReviewed application/pdf en http://eprints.utm.my/8711/1/SarjonDefit2000_PredictiveDataMiningBasedOnSimilarity.pdf Defit, Sarjon and Md. Sap, Mohd. Noor (2000) Predictive data mining based on similarity and clustering methods. Jurnal Teknologi Maklumat, 12 (2). pp. 55-74. ISSN 0128-3790 http://portal.psz.utm.my/psz/index.php?option=com_content&task=view&id=128&Itemid=305&PHPSESSID=81b664e998055f65b4ccff8f61bf7cb2
spellingShingle QA75 Electronic computers. Computer science
Defit, Sarjon
Md. Sap, Mohd. Noor
Predictive data mining based on similarity and clustering methods.
title Predictive data mining based on similarity and clustering methods.
title_full Predictive data mining based on similarity and clustering methods.
title_fullStr Predictive data mining based on similarity and clustering methods.
title_full_unstemmed Predictive data mining based on similarity and clustering methods.
title_short Predictive data mining based on similarity and clustering methods.
title_sort predictive data mining based on similarity and clustering methods
topic QA75 Electronic computers. Computer science
url http://eprints.utm.my/8711/1/SarjonDefit2000_PredictiveDataMiningBasedOnSimilarity.pdf
work_keys_str_mv AT defitsarjon predictivedataminingbasedonsimilarityandclusteringmethods
AT mdsapmohdnoor predictivedataminingbasedonsimilarityandclusteringmethods