Multiple Kernel Probabilistic Clustering with Crow Lion Neural Network for Missing Data Imputation and Classification

30 Pages Posted: 19 Jun 2018

See all articles by Sudha Dr.T.

Sudha Dr.T.

Sri Padmavati Mahila Visvavidyalayam (SPMVV) - Department of Computer Science and Engineering

R. Rajani

Narayana Engineering College - Department of Computer Applications (MCA)

Date Written: February 7, 2018

Abstract

In pattern classification, one of the major problems is the missing data or data incompleteness, which is caused by different reasons. The amount of missing data varies depending on the applications. Missing data imputation is a technique used to handle the missing data problem by utilizing various techniques. The missing data imputation techniques replace the missing values by the estimated values. Numerous techniques are proposed for handling the missing data problem. Accordingly, this paper presents the missing data imputation and classification techniques for handling the missing values presented in the data set. Missing data imputation and classification is proposed by integrating the Multiple Kernel Probabilistic Clustering Algorithm (MKPCA) with Feed Crow Lion neural network (CLNN).

Keywords: data Imputation, Multiple Kernel Probabilistic Clustering Algorithm, Feed Crow Lion neural network

Suggested Citation

Dr.T., Sudha and Rajani, R., Multiple Kernel Probabilistic Clustering with Crow Lion Neural Network for Missing Data Imputation and Classification (February 7, 2018). 2018 IADS International Conference on Computing, Communications & Data Engineering (CCODE), Available at SSRN: https://ssrn.com/abstract=3194390 or http://dx.doi.org/10.2139/ssrn.3194390

Sudha Dr.T. (Contact Author)

Sri Padmavati Mahila Visvavidyalayam (SPMVV) - Department of Computer Science and Engineering ( email )

Padmavathi Nagar, Near West Railway Station,
Andhra Pradesh
Tirupati, Andhra Pradesh 517502
India

R. Rajani

Narayana Engineering College - Department of Computer Applications (MCA)

Andhra Pradesh
India

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