diff --git a/doc/developers/index.rst b/doc/developers/index.rst index 9aaa75ff8c467d01611e733bf175fb1e17f0b3ad..f741e4e7db44b0faae9e24c4568a00d62883d9d7 100644 --- a/doc/developers/index.rst +++ b/doc/developers/index.rst @@ -232,6 +232,7 @@ articles, link to us from your website, or simply by saying "I use it": .. raw:: html + <script type="text/javascript" src="http://www.ohloh.net/p/480792/widgets/project_users.js?style=rainbow"></script> diff --git a/sklearn/manifold/locally_linear.py b/sklearn/manifold/locally_linear.py index 8ba68d98765626da2e40515f948883db5f1947a5..d5b1bfabdd720a8025b681eeb0143e82cd00f33b 100644 --- a/sklearn/manifold/locally_linear.py +++ b/sklearn/manifold/locally_linear.py @@ -191,12 +191,13 @@ def locally_linear_embedding( regularization constant, multiplies the trace of the local covariance matrix of the distances. - eigen_solver : string, {'auto', 'arpack', 'dense'} auto : algorithm will attempt to choose the best method for input data + arpack : use arnoldi iteration in shift-invert mode. For this method, M may be a dense matrix, sparse matrix, or general linear operator. + dense : use standard dense matrix operations for the eigenvalue decomposition. For this method, M must be an array or matrix type. This method should be avoided for @@ -496,9 +497,11 @@ class LocallyLinearEmbedding(BaseEstimator): eigen_solver : string, {'auto', 'arpack', 'dense'} auto : algorithm will attempt to choose the best method for input data + arpack : use arnoldi iteration in shift-invert mode. For this method, M may be a dense matrix, sparse matrix, or general linear operator. + dense : use standard dense matrix operations for the eigenvalue decomposition. For this method, M must be an array or matrix type. This method should be avoided for