# HG changeset patch
# User bshanks@bshanks.dyndns.org
# Date 1239618702 25200
# Node ID 01c118d1074ba2bb3c2a6bcf05cace1ae0e4b9da
# Parent  5db0420abbb6426c36371d724b77a50d5c5f5048
.

--- a/grant.html	Mon Apr 13 03:25:42 2009 -0700
+++ b/grant.html	Mon Apr 13 03:31:42 2009 -0700
@@ -52,7 +52,7 @@
             gene expression dataset used in the construction of the classifier is called training
             data.
                In the machine learning literature, this sort of procedure may be thought
-            of as a supervised learning task, defined as a task in whcih the goal is to learn
+            of as a supervised learning task, defined as a task in which the goal is to learn
             a mapping from instances to labels, and the training data consists of a set of
             instances (voxels) for which the labels (subregions) are known.
                Each gene expression level is called a feature, and the selection of which
@@ -489,6 +489,7 @@
 app2 has examples of genetic targeting to specific anatomical regions
     —
     note:
+    do we need to cite: no known markers? impressive results?
                                             14
 
 
Binary file grant.odt has changed
Binary file grant.pdf has changed
--- a/grant.txt	Mon Apr 13 03:25:42 2009 -0700
+++ b/grant.txt	Mon Apr 13 03:31:42 2009 -0700
@@ -29,7 +29,7 @@
 
 The object of aim 1 is not to produce a single classifier, but rather to develop an automated method for determining a classifier for any known anatomical structure. Therefore, we seek a procedure by which a gene expression dataset may be analyzed in concert with an anatomical atlas in order to produce a classifier. Such a procedure is a type of a machine learning procedure. The construction of the classifier is called __training__ (also __learning__), and the initial gene expression dataset used in the construction of the classifier is called __training data__.
 
-In the machine learning literature, this sort of procedure may be thought of as a __supervised learning task__, defined as a task in whcih the goal is to learn a mapping from instances to labels, and the training data consists of a set of instances (voxels) for which the labels (subregions) are known. 
+In the machine learning literature, this sort of procedure may be thought of as a __supervised learning task__, defined as a task in which the goal is to learn a mapping from instances to labels, and the training data consists of a set of instances (voxels) for which the labels (subregions) are known. 
 
 Each gene expression level is called a __feature__, and the selection of which genes to include is called __feature selection__. Feature selection is one component of the task of learning a classifier. Some methods for learning classifiers start out with a separate feature selection phase, whereas other methods combine feature selection with other aspects of training. 
 
@@ -316,3 +316,5 @@
 ---
 
 note: 
+
+do we need to cite: no known markers? impressive results?