modest update to CLASSIFY_DETAILS.txt

Hi, All.

I'm back to looking at CRM114, and I decided to update some of the
documentation, working from "the (possibly) slightly unstable latest
mainline version" -- thanks for the continued good work, and I hope the 
updates prove useful.  This is the first.

/Jskud

--- crm114-20120205-ORIG/CLASSIFY_DETAILS.txt	2009-09-11 11:25:57.000000000 -0700
+++ crm114-20120205/CLASSIFY_DETAILS.txt	2012-02-06 07:49:00.000000000 -0800
@@ -18,7 +18,8 @@
 The current distribution builds in this set of classifiers.  The
 classifiers are:
 
-1) SBPH Markovian (the default) This is an extension of Bayesian
+1) SBPH Markovian (the default) - This classifier uses
+   Sparse Binary Polynomial Hashing (SBPH), an extension of Bayesian
    classification, mapping features in the input text into a Markov
    Random Field.  This turns each token in the input into 2^(N-1)
    features, which gives high accuracy but at high computation
@@ -52,7 +53,7 @@
    other classifiers.  It _will_ work against binary files, though,
    which none of the other classifiers will.
 
-5) Hyperspatial classification - this experimental classifier
+5) Hyperspatial classification - This experimental classifier
    tokenizes, but does not use Bayes law at all, nor statistical
    "clumping".  During learning, each example document generates a
    single point in a 4 billion dimensional hyperspace.  The
@@ -719,7 +720,7 @@
 
 
 
-The format of a SBPH or OSB Markovian .css file (and, for winnow a
+The format of a SBPH or OSB Markovian .css file (and, for Winnow a
 .cow file) is a 64-bit hash of a feature (whether the feature is a
 single word, a bigram, or a full SBPH does not matter) and a 32-bit
 representation of the value.  In .css files, the 32 bits is an

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