Reliance Stock Market Analysis with RBF Kernel using Support Vector Machine

This paper analyzes stock market prediction using Machine Learning Techniques with varied algorithms. Financial prediction experts consider stock market forecasting to be a difficult endeavor. Different models of Supervised machine learning are used for the prediction of stock prices including the RBF Kernel Model of SVM. In SVM (support vector machines) Linear, polynomial, and RBF models are used. The reliance industry dataset has been used to train the models. After the implementation of SVM highest accuracy is provided by the RBF model which is 95% accuracy. In conclusion, results provided by the RBF model can be preferred for investment, Meanwhile, linear and polynomial models are also used which gave an accuracy of 94% and 93%, and are suitable for investing purposes.