


HIT_ESTIMATE_CS Estimate the best mode number and/or the best size of LDs within a given range ------------------------------------------------------------------------- DESCRIPTION ------------------------------------------------------------------------- [idmodes,F,xi,LDs,inliers]=hit_regression(Xid,yid) ------------------------------------------------------------------------- INPUT ------------------------------------------------------------------------- Xid: matrix containing the regressors. Each row is a datapoint. yid: column vector containing the output datapoints. Xv: matrix containing validation regressors. Each row is a datapoint. yv: column vector containing the validation output datapoints. c_test: vector of integers collecting the values of idpar.c (the LD size) to try. s_test: vector of integers collecting the values of idpar.s (the number of modes) to try. ------------------------------------------------------------------------- OUTPUT ------------------------------------------------------------------------- best_c, best_s: the joint combination of LD size and mode number that minimizes the MSE on validation data. mse_m(i,j): MSE on validation data when using LD size equal to c_test(i) and number of modes equal to s_test(i).
