Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4794
Title: A constructive approach for classification of Semi-Labeled data by extending the BLTA algorithm
Authors: Tiwari, Aruna
Chaudhari, Narendra S.
Keywords: Benchmark datasets;Constructive approach;Generalization accuracy;Labeled data;Layered neural network;Perceptron;Unlabeled samples;Learning algorithms;Network layers;Telecommunication networks;Neural networks
Issue Date: 2010
Citation: Chandel, A. S., Tiwari, A., & Chaudhari, N. S. (2010). A constructive approach for classification of semi-labeled data by extending the BLTA algorithm. Paper presented at the Proceedings - 2010 International Conference on Computational Intelligence and Communication Networks, CICN 2010, 588-590. doi:10.1109/CICN.2010.116
Abstract: In this paper BLTA is extended to tackle the classification of Semi-Labeled data. BLTA works for Labeled data and perceptron based 4-layered neural network structure is formed. In our proposed extension, this 4-layered neural network structure works for classification of Semi-Labeled data, some samples are labeled and some are unlabeled. Learning algorithm is modified to tackle with such samples. The proposed method works in two phases. In first phase labeled samples are used for learning and another phase makes use of unlabeled samples to properly learn them in decided neuron. The proposed algorithm is tested with various benchmark datasets. Results are presented in the form of number of neurons and generalization accuracies. The accuracies are varying from 45 to 98% for different values of M-circle. © 2010 IEEE.
URI: https://doi.org/10.1109/CICN.2010.116
https://dspace.iiti.ac.in/handle/123456789/4794
ISBN: 9780769542546
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

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