MISSING VALUE IMPUTATION AND NORMALIZATION TECHNIQUES IN MYOCARDIAL INFARCTION

Autor:	K Manimekalai, A Kavitha
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	Mean Hot Deck KNN BPCA KNBP Min-Max Algorithm Z-Score Decimal Scaling Computer engineering. Computer hardware TK7885-7895
Zdroj:	ICTACT Journal on Soft Computing, Vol 8, Iss 3, Pp 1655-1662 (2018)
Druh dokumentu:	article
ISSN:	0976-6561 2229-6956
DOI:	10.21917/ijsc.2018.0230
Popis:	Missing Data imputation is an important research topic in data mining. In general, real data contains missing values. The presence of the missing value in the data set has a major problem for precise prediction. The objective of this paper is to highlight possible improvement of existing algorithm for medical data. KNBP imputation method based on KNN and BPCA is proposed and evaluate MSE and RMSE estimates. Normalization is done by comparing three algorithms namely min-max normalization, Z-score and decimal scaling. The experiment is done with standard bench mark data and real time collected data. KNBP imputation method and Decimal Scaling Algorithm for Normalization got lower error rate.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/a41be5d4b6d44d72a0f57e7fd013e954 Zobrazit plný text záznamu View record in DOAJ