Ramya R. currently serves as the Assistant Professor at the Department of Computer Science Engineering at Amrita School of Engineering, Amritapuri. She  has completed an M. Tech in Computer Information Systems.


Publication Type: Conference Paper

Year of Publication Publication Type Title


Conference Paper

K. D. Adeena and R. Remya, “Extraction of relevant dataset for support vector machine training: A comparison”, in 2015 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015, 2015, pp. 222-227.[Abstract]

Support Vector Machine (SVM) is a popular machine learning technique for classification. SVM is computationally infeasible with large dataset due to its large training time. In this paper we compare three different methods for training time reduction of SVM. Different combination of Decision Tree (DT), Fisher Linear Discriminant (FLD), QR Decomposition (QRD) and Modified Fisher Linear Discriminant (MFLD) makes reduced dataset for SVM training. Experimental results indicates that SVM with QRD and MFLD have good classification accuracy with significantly smaller training time. © 2015 IEEE.

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Conference Paper

R. Remya, R.Chandran Lekshmi, and L, N. J., “Design and Simulation of a Single-Stage Half-Bridge AC-DC Converter for Power Factor Correction”, in International Conference On Computation Of Power, Energy, Information and Communication (ICCPEIC), 2014.

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