sort eigvecs in lda

rasbt · Dec 3, 2018 · cc90313 · cc90313
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diff --git a/docs/sources/CHANGELOG.md b/docs/sources/CHANGELOG.md
@@ -22,9 +22,10 @@ The CHANGELOG for the current development version is available at
 
 - Changed the default solver in `PrincipalComponentAnalysis` to `'svd'` instead of `'eigen'` to improve numerical stability. ([#474](https://github.com/rasbt/mlxtend/pull/474))
 
+
 ##### Bug Fixes
 
-- -
+- The eigenvectors maybe have not been sorted in certain edge cases in `LinearDiscriminantAnalysis`. ([#478](https://github.com/rasbt/mlxtend/pull/478))
 
 
 

diff --git a/mlxtend/feature_extraction/linear_discriminant_analysis.py b/mlxtend/feature_extraction/linear_discriminant_analysis.py
@@ -145,7 +145,7 @@ def _eigendecom(self, within_scatter, between_scatter):
         e_vals, e_vecs = np.linalg.eig(np.linalg.inv(within_scatter).dot(
             between_scatter))
         sort_idx = np.argsort(e_vals)[::-1]
-        e_vals, e_vecs = e_vals[sort_idx], e_vecs[sort_idx]
+        e_vals, e_vecs = e_vals[sort_idx], e_vecs[:, sort_idx]
         return e_vals, e_vecs
 
     def _projection_matrix(self, eig_vals, eig_vecs, n_discriminants):