def do_single(r): global training_x, training_y, testing_x, testing_y wl1, wl2 = doTrain(_g_M, _g_eta, r, _g_T, training_x.copy(), training_y.copy()) eout = predict(wl1, wl2, testing_x.copy(), testing_y.copy()) print "r:", r, ", eout:", eout return r, eout
def do_single(M): global training_x, training_y, testing_x, testing_y wl1, wl2 = doTrain(M, _g_eta, _g_w_value_range, _g_T, training_x.copy(), training_y.copy()) eout = predict(wl1, wl2, testing_x.copy(), testing_y.copy()) return M, eout