This project compares the performance of SOM versus LVQ in classification problems. Given two data sets: ‘iris.dat’ has 150 patterns of 3 classes with 4 features. ‘wine.dat’ has 178 patterns of 3 classes with 13 features. For SOM, use its alg

Principal component analysis,for study about classification data,develop for svm , lvq etc-Principal component analysis,for study about classification data,develop for svm , lvq etc

Abstract— Identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limite

Learning Vector Quantization (LVQ) and k-Nearest Neighbor for Intrusion Classification