| SVM trade-off between maximize the margin and minimize the variables used for regression M Premalatha, CV Lakshmi International Journal of Pure and Applied Mathematics 87 (6), 741-750, 2013 | 13 | 2013 |
| SVM approach for non-parametric method in classification and regression learning process on feature selection with ε-insensitive region M Premalatha, C Vijayalakshmi, C Vijayalakshmi Malaya Journal of Matematik. S 276 (279), 10.26637, 2019 | 5 | 2019 |
| SVM approach for classification and regression with absolute value combination method for controlling complexity M Premalatha, CV Lakshmi International Conference on Mathematical Computer Engineering-ICMCE, 533, 2013 | 5 | 2013 |
| A Comparative Analysis of Machine Learning Approaches for State-of-Charge Forecasting for Enhancing Lithium-ion Battery Management in Electric Vehicles TP Balakrishnan, S Sasikumar, M Premalatha, R Amirthavalli, A Rajkumar Nanotechnology Perceptions, 260–273-260–273, 2024 | | 2024 |
| Generalized hendecagonal fuzzy number M Premalatha, A Jeeva, A Selvaraj, S Karthik AIP Conference Proceedings 2853 (1), 2024 | | 2024 |
| Strategic Decision-Making Enhancement Framework (SDE-Framework): Leveraging Neutrosophic Logic and Fuzzy Mathematics for Optimized Outcomes in IT Management and Computational … GJ Manjula, SK Mohiddin, AP Pushpalatha, V Srinivas, M Premalatha, ... International Journal of Neutrosophic Science, 179-79-189, 2024 | | 2024 |
| Optimization of Neutrosophic EOQ Model for Effective Demand Management in Uncertain Environment Using Genetic Optimization GJ Manjula, N Anitha, AP Pushpalatha, KV Laxmi, M Premalatha, ... International Journal of Neutrosophic Science, 56-6-64, 2024 | | 2024 |
| Weighted Support Vector Machine Classification by using Confidence Parameters for Unbalanced Sampling Target Data Sets M Premalatha, C Vijayalakshmi Recent Trends in Computational Intelligence and Its Application, 346-351, 2023 | | 2023 |
| Progressive approach of Machine Learning Algorithm in Neural Nets separable patterns based on SVM classification CV M. Premalatha European Chemical Bulletin 12 (23), 4420-4425, 2023 | | 2023 |
| Randomly Selection of Interior Points in SV Learning Algorithm Uses of Confidence Parameter M Premalatha, C Vijayalakshmi Proceedings of 2nd International Conference on Mathematical Modeling and …, 2022 | | 2022 |
| Implementation of SVM Discriminant model for Irregular shaped classes with best parameter C and γ CV M Premalatha International Journal of Applied Engineering Research 9 (26), 8925-8928, 2014 | | 2014 |
| Support Vector Approach for Classification and Regression Problems in Misclassified data produce in sparse solution CV M Premalatha GJEDT 3 (2), 928-933, 2014 | | 2014 |
| Learning Algorithm of SVM Reduce the Optimization Error and Give the Maximum Accuracy of the QP CV M Premalatha IJAR 4 (4), 387-391, 2014 | | 2014 |
| Mathematical Modeling Based on Neural Network with Fuzzy Logic CV M Premalatha IJARCSSE 4 (3), 928-933, 2014 | | 2014 |
| Machine Learning Techniques for SVM Classification and Regression Loss Function CV M Premalatha IJAIS&ML 3 (7), 483-490, 2011 | | 2011 |
| SV MACHINES FOR FUNCTION ESTIMATION COVERING QUADRATIC PROGRAMMING WITH LARGE DATA SETS USING FOR INTERIOR POINT ALGORITHM M Premalatha, C VijayaLakshmi | | |
| Numerical Analysis of Classifier Based on Various Methods of Clustering in Machine Learning M Premalatha, C Vijayalakshmi Proceedings of the National Conference on Recent Trends in Mathematical …, 0 | | |
