Support Vector Machine-Based Scheme Identification System for the Marginalized People

Scheme identification system is required to improve the socio-economic status of marginalized people. The absence technological innovations creates more complications during online scheme identifications for development In order increases service availability people, a proposed. this, previous beneficiary data collected from Kerala state SC, women and Handicapped Persons cooperation are used. Support Vector Machine (SVM) with linear non-linear kernels identifies best suitable schemes based on input features. Finally, SVM Gaussian Radial Basis Function (RBF) kernel achieved 91.23 %, 95.65% 94.23% accuracy Women data.