--- a/doc/v2_planning/main_plan.txt	Wed Sep 08 14:26:35 2010 -0400
+++ b/doc/v2_planning/main_plan.txt	Wed Sep 08 15:39:51 2010 -0400
@@ -234,40 +234,6 @@
 For each thing with a functional spec (e.g. datasets library, optimization library) make a
 separate file.
 
-
-
-pylearn.formulas
-----------------
-
-Directory with functions for building layers, calculating classification
-errors, cross-entropies with various distributions, free energies, etc.  This
-module would include for the most part global functions, Theano Ops and Theano
-optimizations.
-
-Yoshua: I would break it down in module files, e.g.:
-
-pylearn.formulas.costs: generic / common cost functions, e.g. various cross-entropies, squared error, 
-abs. error, various sparsity penalties (L1, Student)
-
-pylearn.formulas.linear: formulas for linear classifier, linear regression, factor analysis, PCA
-
-pylearn.formulas.nnet: formulas for building layers of various kinds, various activation functions,
-layers which could be plugged with various costs & penalties, and stacked
-
-pylearn.formulas.ae: formulas for auto-encoders and denoising auto-encoder variants
-
-pylearn.formulas.noise: formulas for corruption processes
-
-pylearn.formulas.rbm: energies, free energies, conditional distributions, Gibbs sampling
-
-pylearn.formulas.trees: formulas for decision trees
-
-pylearn.formulas.boosting: formulas for boosting variants
-
-etc.
-
-Fred: It seam that the DeepANN git repository by Xavier G. have part of this as function.
-
 Indexing Convention
 ~~~~~~~~~~~~~~~~~~~