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Date: 2010
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/148096
Description: This paper develops a model for short-term prediction of time series based on Element Oriented Analysis (EOA). The EOA model represents nonlinear changes in a time series as strata and uses these in d ... More
Reviewed: Reviewed
Date: 2010
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/323549
Description: In this paper, we present an application of an Element Oriented Analysis (EOA) credit scoring model used as a classifier for assessing the bad risk records. The model building methodology we used is t ... More
Reviewed: Reviewed
Date: 2008
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/148864
Description: Mining multidimensional data has two major concerns. One is how to select the most salient attributes and another one is how to guarantee the precision of mining results. This paper introduces a novel ... More
Reviewed: Reviewed
Date: 2007
Language: eng
Resource Type: journal article
Identifier: http://hdl.handle.net/1959.14/1140161
Description: Unsupervised learning plays an important role in the Knowlede exploration discovery. The basic task of unsupervised learning is to find latent variablesor relationships in a given dataset wihout any a ... More
Reviewed: Reviewed
Date: 2006
Language: eng
Resource Type: book chapter
Identifier: http://hdl.handle.net/1959.14/19491
Description: This paper describes a time-changing feature selection1 framework based on hierachical distribution method for extracting knowledge from health records. In the framework, we propose three steps for ti ... More
Date: 2006
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/17754
Description: Unsupervised learning plays an important role in knowledge exploration and discovery. Two basic examples of unsupervised learning are clustering and dimensionality reduction. In this paper, we introdu ... More
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Date: 2004
Language: eng
Resource Type: book chapter
Identifier: http://hdl.handle.net/1959.14/347037
Description: This study proposes a temporal data mining method to discover qualitative and quantitative patterns in time series databases. The method performs discrete-valued time series (DIS) analysis on time ser ... More
Date: 2001
Language: eng
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.14/19089
Description: This study proposes a data mining framework to discover qualitative and quantitative patterns in discrete-valued time series (DTS). In our method, there are three levels for mining similarity and peri ... More
Reviewed: Reviewed
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