Python GaussianKernel.ridge_regress Beispiele

Beispiel #1

def disRe(par,lnd_cho,X,Y,Xtst=None,Ytst = None):
	mu_tr  = pln_ebeding(par[0],X,lnd_cho)

	kernel = GaussianKernel(float(par[1]))
	if Xtst is None:
		beta = kernel.ridge_regress(mu_tr,Y,par[2])

	else:
		mu_tt = pln_ebeding(par[0],Xtst,lnd_cho)
		if Ytst is None:
			beta,prdt = kernel.ridge_regress(mu_tr,Y,par[2],mu_tt)
		else:
			beta,prdt,mse = kernel.ridge_regress(mu_tr,Y,par[2], mu_tt, Ytst)
	return beta,prdt,np.sqrt(mse)

Beispiel #2

def disRe_corc(par,eta,lnd_cho,X,Y,Xtst = None,Ytst = None):
	mu_tr,sigma_tr = bag_cor(par[0],eta,X,lnd_cho)

	kernel = GaussianKernel(float(par[1]))
	if Xtst is None:
		beta = kernel.ridge_regress(mu_tr,Y,par[2])

	else:
		mu_tt,sigma_tt = bag_cor(par[0],eta,Xtst,lnd_cho)
		if Ytst is None:
			beta,prdt = kernel.ridge_regress(mu_tr,Y,par[2],mu_tt)
		else:
			beta,prdt,mse = kernel.ridge_regress(mu_tr,Y,par[2],mu_tt,Ytst)
	return beta,prdt,np.sqrt(mse)

Beispiel #3

Datei: RFF1.py Projekt: Mick116/D-Regression

def err_pre(xs,ys,xt,yt,sgma = 1.0,lamda = 0.1):
    kernel = GaussianKernel(float(sgma))
    aa,y_pre,err_pre0 = kernel.ridge_regress(xs,ys,lamda,Xtst=xt,ytst=yt)
    return y_pre,err_pre0