Adaptive Learning, Stock Market, Predictions, Machine Learning, Artificial Intelligence.
plt The next step is the implementation of LMSPred, you can try by yourself while looking to the pseudocode, here is my implementation: def lmsPred(x,l,u,N): xd= np.block([np.zeros((1,l)), x]).T y=np.zeros((len(xd),1)) xn=np.zeros((N+1,1)) xn = np.matrix(xn) wn=np.random.rand(N+1,1)/10 M=len(xd)