svn commit: r455065 - head/devel/py-naiveBayesClassifier

[Dan Langille]

Author: dvl
Date: Tue Nov 28 17:08:45 2017
New Revision: 455065
URL: https://svnweb.freebsd.org/changeset/ports/455065

Log:
  Provide a better description of what this is.
  
  Reported by:	Alexy Dokuchaev & Adam Weinberger

Modified:
  head/devel/py-naiveBayesClassifier/Makefile
  head/devel/py-naiveBayesClassifier/pkg-descr

Modified: head/devel/py-naiveBayesClassifier/Makefile
==============================================================================
--- head/devel/py-naiveBayesClassifier/Makefile	Tue Nov 28 16:57:42 2017	(r455064)
+++ head/devel/py-naiveBayesClassifier/Makefile	Tue Nov 28 17:08:45 2017	(r455065)
@@ -3,6 +3,7 @@
 
 PORTNAME=	naiveBayesClassifier
 PORTVERSION=	0.1.3
+PORTREVISION=	1
 CATEGORIES=	devel python
 MASTER_SITES=	CHEESESHOP
 PKGNAMEPREFIX=	${PYTHON_PKGNAMEPREFIX}

Modified: head/devel/py-naiveBayesClassifier/pkg-descr
==============================================================================
--- head/devel/py-naiveBayesClassifier/pkg-descr	Tue Nov 28 16:57:42 2017	(r455064)
+++ head/devel/py-naiveBayesClassifier/pkg-descr	Tue Nov 28 17:08:45 2017	(r455065)
@@ -1,4 +1,21 @@
-yet another general purpose Naive Bayesian classifier.
+Yet another general purpose Naive Bayesian classifier.
 (under heavy development)
+
+Naive Bayes Classifier is probably the most widely used text classifier, 
+it's a supervised learning algorithm. It can be used to classify blog posts
+or news articles into different categories like sports, entertainment and
+so forth. 
+
+Naive Bayes is a simple technique for constructing classifiers: models that
+assign class labels to problem instances, represented as vectors of feature
+values, where the class labels are drawn from some finite set. It is not a
+single algorithm for training such classifiers, but a family of algorithms
+based on a common principle: all naive Bayes classifiers assume that the value
+of a particular feature is independent of the value of any other feature,
+given the class variable. For example, a fruit may be considered to be an apple
+if it is red, round, and about 10 cm in diameter. A naive Bayes classifier
+considers each of these features to contribute independently to the probability
+that this fruit is an apple, regardless of any possible correlations between
+the color, roundness, and diameter features.
 
 WWW: https://pypi.python.org/pypi/naiveBayesClassifier