diff --git a/qstack/regression/cross-validate_results.py b/qstack/regression/cross-validate_results.py
index 60640ca..19b961a 100755
--- a/qstack/regression/cross-validate_results.py
+++ b/qstack/regression/cross-validate_results.py
@@ -13,7 +13,7 @@
 
 
 def cv(X, y,
-           sigma=defaults.sigmaarr, eta=defaults.etaarr, gkernel=defaults.gkernel, gdict=defaults.gdict,
+           sigmaarr=defaults.sigmaarr, etaarr=defaults.etaarr, gkernel=defaults.gkernel, gdict=defaults.gdict,
            akernel=defaults.kernel, test_size=defaults.test_size, train_size=defaults.train_size, splits=defaults.splits,
            printlevel=0, adaptive=False, read_kernel=False, ipywidget=None, n_rep=defaults.n_rep, save=False, preffix='uknown'):
     hyper_runs = []
@@ -23,13 +23,17 @@ def cv(X, y,
     if bar > 0:
         progress = utt.add_progressbar(max_value=n_rep)
     for seed,n in zip(seeds, range(n_rep)):
-        error = hyperparameters(X, y, read_kernel=False, sigma=sigma, eta=eta, akernel=akernel, test_size=test_size, splits=splits, printlevel=printlevel, adaptive=adaptive, debug=seed)
+        error = hyperparameters(X, y, read_kernel=False, sigma=sigmaarr, eta=etaarr, akernel=akernel, test_size=test_size, splits=splits, printlevel=printlevel, adaptive=adaptive, debug=seed)
         mae, stdev, eta, sigma = zip(*error)
-        hyper_runs.append(list(zip([n]*len(error), error, stdev, eta, sigma)))
         maes_all = regression(X, y, read_kernel=False, sigma=sigma[-1], eta=eta[-1], akernel=akernel, test_size=test_size, train_size=train_size, n_rep=1, debug=seed)
+        ind = np.argsort(error[:,3])
+        error = error[ind]
+        ind = np.argsort(error[:,2])
+        error = error[ind]
+        hyper_runs.append(error)
         lc_runs.append(maes_all)
         if bar > 0:
-            progress.update(n)
+            progress.update(n+1)
     lc_runs = np.array(lc_runs)
     hyper_runs = np.array(hyper_runs, dtype=object)
     lc = list(zip(lc_runs[:,:,0].mean(axis=0), lc_runs[:,:,1].mean(axis=0), lc_runs[:,:,1].std(axis=0), lc_runs[:,:,3].mean(axis=0)))
@@ -76,7 +80,7 @@ def main():
         selected = np.loadtxt(args.f_select, dtype=int)
         X = X[selected]
         y = y[selected]
-    final = cv(X, y, sigma=args.sigma, eta=args.eta, akernel=args.akernel, test_size=args.test_size, splits=args.splits, printlevel=args.printlevel, adaptive=args.adaptive, train_size=args.train_size, n_rep=args.n_rep, preffix=args.nameout, save=args.save_all)
+    final = cv(X, y, sigmaarr=args.sigma, etaarr=args.eta, akernel=args.akernel, test_size=args.test_size, splits=args.splits, printlevel=args.printlevel, adaptive=args.adaptive, train_size=args.train_size, n_rep=args.n_rep, preffix=args.nameout, save=args.save_all)
     print(final)
     np.savetxt(args.nameout, final)