From f7042f832b33c7ad44295266a5932710c6b4b735 Mon Sep 17 00:00:00 2001
From: Farid Mohammadi <farid.mohammadi@iws.uni-stuttgart.de>
Date: Mon, 1 Aug 2022 08:48:30 +0200
Subject: [PATCH] [surrogate] comment the refitting with the bias term.
---
.../surrogate_models/surrogate_models.py | 24 +++++++++----------
1 file changed, 12 insertions(+), 12 deletions(-)
diff --git a/src/bayesvalidrox/surrogate_models/surrogate_models.py b/src/bayesvalidrox/surrogate_models/surrogate_models.py
index f478bbd5e..722221d74 100644
--- a/src/bayesvalidrox/surrogate_models/surrogate_models.py
+++ b/src/bayesvalidrox/surrogate_models/surrogate_models.py
@@ -701,18 +701,18 @@ class MetaModel():
# The first column must be kept (For mean calculations)
nnz_idx = np.nonzero(clf_poly.coef_)[0]
- if len(nnz_idx) == 0 or nnz_idx[0] != 0:
- nnz_idx = np.insert(np.nonzero(clf_poly.coef_)[0], 0, 0)
- # Remove the zero entries for Bases and PSI if need be
- if sparsity:
- sparse_basis_indices = basis_indices.toarray()[nnz_idx]
- else:
- sparse_basis_indices = basis_indices[nnz_idx]
- sparse_X = X[:, nnz_idx]
-
- # Store the coefficients of the regression model
- clf_poly.fit(sparse_X, y)
- coeffs = clf_poly.coef_
+ # if len(nnz_idx) == 0 or nnz_idx[0] != 0:
+ # nnz_idx = np.insert(np.nonzero(clf_poly.coef_)[0], 0, 0)
+ # # Remove the zero entries for Bases and PSI if need be
+ # if sparsity:
+ # sparse_basis_indices = basis_indices.toarray()[nnz_idx]
+ # else:
+ # sparse_basis_indices = basis_indices[nnz_idx]
+ # sparse_X = X[:, nnz_idx]
+
+ # # Store the coefficients of the regression model
+ # clf_poly.fit(sparse_X, y)
+ # coeffs = clf_poly.coef_
# This is for the case where all outputs are zero, thereby
# all coefficients are zero
--
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