jens/Rbm-legacy
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

- use normalize per training sample

Browse Source 
git-svn-id: http://moon:8086/svn/software/trunk/projects/RBM@555 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
jens
2019-10-18 06:16:27 +00:00
parent 2c2039ec2f
commit ea6a1ee6ed
1 changed files with 15 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files
Source/Rbm.cpp
+15 -2
View File
@@ -66,7 +66,7 @@ MatrixXd Rbm::sample(MatrixXd const &src)
noiseUniform(n); noiseUniform(n);
return (src.array() > n.array()).cast<double>(); return (src.array() >= n.array()).cast<double>();
} }
void Rbm::sample(MatrixXd &dst, MatrixXd const &src) void Rbm::sample(MatrixXd &dst, MatrixXd const &src)
@@ -86,6 +86,7 @@ RowVectorXd Rbm::probsLogistic(RowVectorXd const &src)
MatrixXd Rbm::normalizeData(MatrixXd const &src) MatrixXd Rbm::normalizeData(MatrixXd const &src)
{ {
#if 0
double mean = src.array().mean(); double mean = src.array().mean();
cout << "mean" << ": " << endl << mean << endl; cout << "mean" << ": " << endl << mean << endl;
@@ -94,7 +95,19 @@ MatrixXd Rbm::normalizeData(MatrixXd const &src)
double stddev = sqrt(x2.array().mean()); double stddev = sqrt(x2.array().mean());
cout << "stddev" << ": " << endl << stddev << endl; cout << "stddev" << ": " << endl << stddev << endl;
return x; return x/stddev;
#else
MatrixXd mean = src.colwise().mean();
MatrixXd x = src - mean.replicate(src.rows(), 1);
MatrixXd x2 = x.cwiseProduct(x);
MatrixXd stddev_inv = x2.colwise().mean();
stddev_inv = stddev_inv.array().sqrt().cwiseInverse();
return x*stddev_inv.replicate(src.rows(), 1);
#endif
} }