FINANCIAL FORECASTING USING DECISION TREE (REPTree & C4.5) AND NEURAL NETWORKS (K*) FOR HANDLING THE MISSING VALUES

Missing values are a widespread problem in data analysis. The purpose of this paper is to design a model to handle the missing values in predicting financial health of companies. Forecasting business failure is an important and challenge task for both academic researchers and business practitioners....

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Main Authors: J Jayanthi, Gurpreet Kaur, K Suresh Joseph
Format: Article
Language:English
Published: ICT Academy of Tamil Nadu 2017-04-01
Series:ICTACT Journal on Soft Computing
Subjects:
Online Access:http://ictactjournals.in/ArticleDetails.aspx?id=3019
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author J Jayanthi
Gurpreet Kaur
K Suresh Joseph
author_facet J Jayanthi
Gurpreet Kaur
K Suresh Joseph
author_sort J Jayanthi
collection DOAJ
description Missing values are a widespread problem in data analysis. The purpose of this paper is to design a model to handle the missing values in predicting financial health of companies. Forecasting business failure is an important and challenge task for both academic researchers and business practitioners. In this study, we compare the classification of accuracy in decision tree methods (REP tree, C4.5) and with ANN method (K*) to handle the missing values.
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spelling doaj.art-a33a39e5a8d44d808c93417c39ec1e852022-12-22T02:21:50ZengICT Academy of Tamil NaduICTACT Journal on Soft Computing0976-65612229-69562017-04-017314731477FINANCIAL FORECASTING USING DECISION TREE (REPTree & C4.5) AND NEURAL NETWORKS (K*) FOR HANDLING THE MISSING VALUESJ Jayanthi0Gurpreet Kaur1K Suresh Joseph2Lovely Professional University, IndiaLovely Professional University, IndiaPondicherry University, IndiaMissing values are a widespread problem in data analysis. The purpose of this paper is to design a model to handle the missing values in predicting financial health of companies. Forecasting business failure is an important and challenge task for both academic researchers and business practitioners. In this study, we compare the classification of accuracy in decision tree methods (REP tree, C4.5) and with ANN method (K*) to handle the missing values.http://ictactjournals.in/ArticleDetails.aspx?id=3019Bankruptcy predictionMissing valuesDecision Tree (REPTreeC4.5)ANN (K*)
spellingShingle J Jayanthi
Gurpreet Kaur
K Suresh Joseph
FINANCIAL FORECASTING USING DECISION TREE (REPTree & C4.5) AND NEURAL NETWORKS (K*) FOR HANDLING THE MISSING VALUES
ICTACT Journal on Soft Computing
Bankruptcy prediction
Missing values
Decision Tree (REPTree
C4.5)
ANN (K*)
title FINANCIAL FORECASTING USING DECISION TREE (REPTree & C4.5) AND NEURAL NETWORKS (K*) FOR HANDLING THE MISSING VALUES
title_full FINANCIAL FORECASTING USING DECISION TREE (REPTree & C4.5) AND NEURAL NETWORKS (K*) FOR HANDLING THE MISSING VALUES
title_fullStr FINANCIAL FORECASTING USING DECISION TREE (REPTree & C4.5) AND NEURAL NETWORKS (K*) FOR HANDLING THE MISSING VALUES
title_full_unstemmed FINANCIAL FORECASTING USING DECISION TREE (REPTree & C4.5) AND NEURAL NETWORKS (K*) FOR HANDLING THE MISSING VALUES
title_short FINANCIAL FORECASTING USING DECISION TREE (REPTree & C4.5) AND NEURAL NETWORKS (K*) FOR HANDLING THE MISSING VALUES
title_sort financial forecasting using decision tree reptree c4 5 and neural networks k for handling the missing values
topic Bankruptcy prediction
Missing values
Decision Tree (REPTree
C4.5)
ANN (K*)
url http://ictactjournals.in/ArticleDetails.aspx?id=3019
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