Narendra Kumar Kamila

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This paper explores the possibility of classification based on Pareto multi-objective optimization. The efforts on solving optimization problems using the Pareto-based MOO methodology have gained increasing impetus on comparison of selected constraints. Moreover we have different types of classification problem based on optimization model like single(More)
This paper addresses the selection of sub-feature from each feature using fuzzy methodologies maintaining the privacy during collection of data from participating parties in distributed environment. Based on fuzzy random variables conditional expectation is used in which two fuzzy sets are generated using Borel set that helps to determine sub-feature within(More)
The feature selection addresses the issue of developing accurate models for classification in data mining. The aggregated data collection from distributed environment for feature selection makes the problem of accessing the relevant inputs of individual data records. Preserving the privacy of individual data is often critical issue in distributed data(More)
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