All Codes are from scratch using basic packages like numpy,pandas etc.
The aim of this project is Stock Market Prediction using LSSVR and optimize the hyperparameters of various kernels using different evolutionary optimizers. Here optimizers used are Particle Swarm Optimizer(PSO)1985 and Salp Swarm optimizers(SSO)2017. We can compare the time taken for both optimizers, and can see how new optimizers perform. Here, the much recent optimizer SSO, is more efficient than PSO. Also can use other kernels like Linear,Sigmoid, Polynomial but we prefer RBF as it is best suited for Time Series Data, and requires two hyperparameter tuning compared to polynomial's four.