update to version 1.4.0

need47 · Nov 5, 2012 · 32fc278 · 32fc278
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diff --git a/ChangeLog b/ChangeLog
@@ -1,3 +1,9 @@
+2012-11-05	v1.4.0
+------------------
+
+  * update according to reviewers' comments
+  * several bug fixes based on users' feedback
+
 2012-05-31	v1.3.1
 ------------------
 

diff --git a/README.md b/README.md
@@ -1,21 +1,22 @@
-FSelector: a Ruby gem for feature selection and ranking
-===========================================================
+FSelector: a Ruby gem for feature selection
+===========================================
 
 **Home**: [https://rubygems.org/gems/fselector](https://rubygems.org/gems/fselector)  
 **Source Code**: [https://github.com/need47/fselector](https://github.com/need47/fselector)  
-**Documentation** [http://rubydoc.info/gems/fselector/frames](http://rubydoc.info/gems/fselector/frames)  
+**Documentation**: [http://rubydoc.info/gems/fselector/frames](http://rubydoc.info/gems/fselector/frames)  
+**Publication**: [Bioinformatics, 2012, 28, 2851-2852](http://bioinformatics.oxfordjournals.org/content/28/21/2851)  
 **Author**: Tiejun Cheng  
 **Email**: [[email protected]](mailto:[email protected])  
 **Copyright**: 2012  
 **License**: MIT License  
-**Latest Version**: 1.3.1  
-**Release Date**: 2012-05-31
+**Latest Version**: 1.4.0  
+**Release Date**: 2012-11-05
 
 Synopsis
 --------
 
 FSelector is a Ruby gem that aims to integrate various feature 
-selection/ranking algorithms and related functions into one single 
+selection algorithms and related functions into one single 
 package. Welcome to contact me ([email protected]) if you'd like to 
 contribute your own algorithms or report a bug. FSelector allows user 
 to perform feature selection by using either a single algorithm or an 
@@ -49,18 +50,18 @@ Feature List
     Accuracy                         Acc         weighting  multi-class    discrete
     AccuracyBalanced                 Acc2        weighting  multi-class    discrete
     BiNormalSeparation               BNS         weighting  multi-class    discrete
-    CFS_d                            CFS_d       subset     multi-class    discrete
+    CFS_d                            CFS_d       searching  multi-class    discrete
     ChiSquaredTest                   CHI         weighting  multi-class    discrete
     CorrelationCoefficient           CC          weighting  multi-class    discrete
     DocumentFrequency                DF          weighting  multi-class    discrete
     F1Measure                        F1          weighting  multi-class    discrete
     FishersExactTest                 FET         weighting  multi-class    discrete
-    FastCorrelationBasedFilter       FCBF        subset     multi-class    discrete
+    FastCorrelationBasedFilter       FCBF        searching  multi-class    discrete
     GiniIndex                        GI          weighting  multi-class    discrete
     GMean                            GM          weighting  multi-class    discrete
     GSSCoefficient                   GSS         weighting  multi-class    discrete
     InformationGain                  IG          weighting  multi-class    discrete
-    INTERACT                         INTERACT    subset     multi-class    discrete
+    INTERACT                         INTERACT    searching  multi-class    discrete
     JMeasure                         JM          weighting  multi-class    discrete
     KLDivergence                     KLD         weighting  multi-class    discrete
     MatthewsCorrelationCoefficient   MCC, PHI    weighting  multi-class    discrete
@@ -78,25 +79,25 @@ Feature List
     Specificity                      SP          weighting  multi-class    discrete
     SymmetricalUncertainty           SU          weighting  multi-class    discrete
     BetweenWithinClassesSumOfSquare  BSS_WSS     weighting  multi-class    continuous
-    CFS_c                            CFS_c       subset     multi-class    continuous
+    CFS_c                            CFS_c       searching  multi-class    continuous
     FTest                            FT          weighting  multi-class    continuous
-    KS_CCBF                          KS_CCBF     subset     multi-class    continuous
+    KS_CCBF                          KS_CCBF     searching  multi-class    continuous
     KSTest                           KST         weighting  two-class      continuous
     PMetric                          PM          weighting  two-class      continuous
     Relief_c                         Relief_c    weighting  two-class      continuous
     ReliefF_c                        ReliefF_c   weighting  multi-class    continuous
     TScore                           TS          weighting  two-class      continuous
     WilcoxonRankSum                  WRS         weighting  two-class      continuous
-    LasVegasFilter                   LVF         subset     multi-class    discrete, continuous, mixed
-    LasVegasIncremental              LVI         subset     multi-class    discrete, continuous, mixed
+    LasVegasFilter                   LVF         searching  multi-class    discrete, continuous, mixed
+    LasVegasIncremental              LVI         searching  multi-class    discrete, continuous, mixed
     Random                           Rand        weighting  multi-class    discrete, continuous, mixed
-    RandomSubset                     RandS       subset     multi-class    discrete, continuous, mixed
+    RandomSubset                     RandS       searching  multi-class    discrete, continuous, mixed
 
   **note for feature selection interface:**   
-  there are two types of filter methods, i.e., feature weighting algorithms and feature subset selection algorithms  
+  there are two types of filter algorithms: filter\_by\_feature\_weighting and filter\_by\_feature\_searching  
 
-  - for weighting type: use either **select\_feature\_by\_score!** or **select\_feature\_by\_rank!**  
-  - for subset type: use **select\_feature!**
+  - for former: use either **select\_feature\_by\_score!** or **select\_feature\_by\_rank!**  
+  - for latter: use **select\_feature!**
 
 **3. feature selection approaches**
 
@@ -205,7 +206,7 @@ Usage
     # an ensemble of 40 feature selectors with 90% data by random sampling
     re = FSelector::EnsembleSingle.new(r, 40, 0.90, :random_sampling)
 
-    # read SPECT data set  (under the test/ directory)
+    # read SPECT data set (under the test/ directory)
     re.data_from_csv('test/SPECT_train.csv')
 
     # number of features before feature selection
@@ -225,7 +226,7 @@ Usage
 	# creating an ensemble of feature selectors by using 
 	# two feature selection algorithms: InformationGain (IG) and Relief_d. 
 	# note: can be 2+ algorithms, as long as they are of the same type, 
-	# either feature weighting or feature subset selection algorithms
+	# either filter_by_feature_weighting or filter_by_feature_searching
 
 	# test for the type of feature weighting algorithms 
     r1 = FSelector::IG.new

diff --git a/doc/Array.html b/doc/Array.html
@@ -967,7 +967,7 @@ <h3>Returns:</h3>
 </div>
 
     <div id="footer">
-  Generated on Thu May 31 14:31:38 2012 by 
+  Generated on Mon Nov  5 11:19:44 2012 by 
   <a href="http://yardoc.org" title="Yay! A Ruby Documentation Tool" target="_parent">yard</a>
   0.7.5 (ruby-1.9.3).
 </div>

diff --git a/doc/Consistency.html b/doc/Consistency.html
@@ -646,7 +646,7 @@ <h3>Returns:</h3>
 </div>
 
     <div id="footer">
-  Generated on Thu May 31 14:31:39 2012 by 
+  Generated on Mon Nov  5 11:19:44 2012 by 
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   0.7.5 (ruby-1.9.3).
 </div>

diff --git a/doc/Discretizer.html b/doc/Discretizer.html
@@ -1250,7 +1250,7 @@ <h3>Parameters:</h3>
 </div>
 
     <div id="footer">
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+  Generated on Mon Nov  5 11:19:44 2012 by 
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   0.7.5 (ruby-1.9.3).
 </div>

diff --git a/doc/Entropy.html b/doc/Entropy.html
@@ -787,7 +787,7 @@ <h3>Returns:</h3>
 </div>
 
     <div id="footer">
-  Generated on Thu May 31 14:31:39 2012 by 
+  Generated on Mon Nov  5 11:19:44 2012 by 
   <a href="http://yardoc.org" title="Yay! A Ruby Documentation Tool" target="_parent">yard</a>
   0.7.5 (ruby-1.9.3).
 </div>

diff --git a/doc/FSelector.html b/doc/FSelector.html
@@ -117,7 +117,7 @@ <h2>Constant Summary</h2>
 
 </div>
         </dt>
-        <dd><pre class="code"><span class='tstring'><span class='tstring_beg'>'</span><span class='tstring_content'>1.3.1</span><span class='tstring_end'>'</span></span></pre></dd>
+        <dd><pre class="code"><span class='tstring'><span class='tstring_beg'>'</span><span class='tstring_content'>1.4.0</span><span class='tstring_end'>'</span></span></pre></dd>
 
         <dt id="Rand-constant" class="">Rand =
           <div class="docstring">
@@ -673,7 +673,7 @@ <h2>Constant Summary</h2>
 </div>
 
     <div id="footer">
-  Generated on Thu May 31 14:31:38 2012 by 
+  Generated on Mon Nov  5 11:19:44 2012 by 
   <a href="http://yardoc.org" title="Yay! A Ruby Documentation Tool" target="_parent">yard</a>
   0.7.5 (ruby-1.9.3).
 </div>

diff --git a/doc/FSelector/Accuracy.html b/doc/FSelector/Accuracy.html
@@ -105,6 +105,8 @@ <h2>Overview</h2><div class="docstring">
        tp+fn+tn+fp     A+B+C+D
 </code></pre>
 
+<p>ref: <a href="http://dl.acm.org/citation.cfm?id=944974">An extensive empirical study of feature selection metrics for text classification</a></p>
+
 
   </div>
 </div>
@@ -199,7 +201,7 @@ <h2>Constructor Details</h2>
 </div>
 
     <div id="footer">
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+  Generated on Mon Nov  5 11:19:45 2012 by 
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   0.7.5 (ruby-1.9.3).
 </div>

diff --git a/doc/FSelector/AccuracyBalanced.html b/doc/FSelector/AccuracyBalanced.html
@@ -199,7 +199,7 @@ <h2>Constructor Details</h2>
 </div>
 
     <div id="footer">
-  Generated on Thu May 31 14:31:41 2012 by 
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diff --git a/doc/FSelector/Base.html b/doc/FSelector/Base.html
@@ -1880,7 +1880,7 @@ <h3>Returns:</h3>
       <pre class="code"><span class="info file"># File 'lib/fselector/algo_base/base.rb', line 345</span>
 
 <span class='kw'>def</span> <span class='id identifier rubyid_select_feature!'>select_feature!</span>
-  <span class='kw'>if</span> <span class='kw'>not</span> <span class='kw'>self</span><span class='period'>.</span><span class='id identifier rubyid_algo_type'>algo_type</span> <span class='op'>==</span> <span class='symbol'>:feature_subset_selection</span>
+  <span class='kw'>if</span> <span class='kw'>not</span> <span class='kw'>self</span><span class='period'>.</span><span class='id identifier rubyid_algo_type'>algo_type</span> <span class='op'>==</span> <span class='symbol'>:filter_by_feature_searching</span>
     <span class='id identifier rubyid_abort'>abort</span> <span class='tstring'><span class='tstring_beg'>&quot;</span><span class='tstring_content'>[</span><span class='embexpr_beg'>#{</span><span class='kw'>__FILE__</span><span class='rbrace'>}</span><span class='tstring_content'>@</span><span class='embexpr_beg'>#{</span><span class='kw'>__LINE__</span><span class='rbrace'>}</span><span class='tstring_content'>]: \n</span><span class='tstring_end'>&quot;</span></span><span class='op'>+</span>
           <span class='tstring'><span class='tstring_beg'>&quot;</span><span class='tstring_content'>  select_feature! is the interface for the type of feature subset selection algorithms only. \n</span><span class='tstring_end'>&quot;</span></span> <span class='op'>+</span>
           <span class='tstring'><span class='tstring_beg'>&quot;</span><span class='tstring_content'>  please consider select_featue_by_score! or select_feature_by_rank!, \n</span><span class='tstring_end'>&quot;</span></span> <span class='op'>+</span>
@@ -2000,7 +2000,7 @@ <h3>Parameters:</h3>
       <pre class="code"><span class="info file"># File 'lib/fselector/algo_base/base.rb', line 413</span>
 
 <span class='kw'>def</span> <span class='id identifier rubyid_select_feature_by_rank!'>select_feature_by_rank!</span><span class='lparen'>(</span><span class='id identifier rubyid_criterion'>criterion</span><span class='comma'>,</span> <span class='id identifier rubyid_my_ranks'>my_ranks</span><span class='op'>=</span><span class='kw'>nil</span><span class='rparen'>)</span>
-  <span class='kw'>if</span> <span class='kw'>not</span> <span class='kw'>self</span><span class='period'>.</span><span class='id identifier rubyid_algo_type'>algo_type</span> <span class='op'>==</span> <span class='symbol'>:feature_weighting</span>
+  <span class='kw'>if</span> <span class='kw'>not</span> <span class='kw'>self</span><span class='period'>.</span><span class='id identifier rubyid_algo_type'>algo_type</span> <span class='op'>==</span> <span class='symbol'>:filter_by_feature_weighting</span>
     <span class='id identifier rubyid_abort'>abort</span> <span class='tstring'><span class='tstring_beg'>&quot;</span><span class='tstring_content'>[</span><span class='embexpr_beg'>#{</span><span class='kw'>__FILE__</span><span class='rbrace'>}</span><span class='tstring_content'>@</span><span class='embexpr_beg'>#{</span><span class='kw'>__LINE__</span><span class='rbrace'>}</span><span class='tstring_content'>]: \n</span><span class='tstring_end'>&quot;</span></span><span class='op'>+</span>
           <span class='tstring'><span class='tstring_beg'>&quot;</span><span class='tstring_content'>  select_feature_by_rank! is the interface for the type of feature weighting algorithms only. \n</span><span class='tstring_end'>&quot;</span></span> <span class='op'>+</span>
           <span class='tstring'><span class='tstring_beg'>&quot;</span><span class='tstring_content'>  please consider select_featue!, \n</span><span class='tstring_end'>&quot;</span></span> <span class='op'>+</span>
@@ -2120,7 +2120,7 @@ <h3>Parameters:</h3>
       <pre class="code"><span class="info file"># File 'lib/fselector/algo_base/base.rb', line 379</span>
 
 <span class='kw'>def</span> <span class='id identifier rubyid_select_feature_by_score!'>select_feature_by_score!</span><span class='lparen'>(</span><span class='id identifier rubyid_criterion'>criterion</span><span class='comma'>,</span> <span class='id identifier rubyid_my_scores'>my_scores</span><span class='op'>=</span><span class='kw'>nil</span><span class='rparen'>)</span>
-  <span class='kw'>if</span> <span class='kw'>not</span> <span class='kw'>self</span><span class='period'>.</span><span class='id identifier rubyid_algo_type'>algo_type</span> <span class='op'>==</span> <span class='symbol'>:feature_weighting</span>
+  <span class='kw'>if</span> <span class='kw'>not</span> <span class='kw'>self</span><span class='period'>.</span><span class='id identifier rubyid_algo_type'>algo_type</span> <span class='op'>==</span> <span class='symbol'>:filter_by_feature_weighting</span>
     <span class='id identifier rubyid_abort'>abort</span> <span class='tstring'><span class='tstring_beg'>&quot;</span><span class='tstring_content'>[</span><span class='embexpr_beg'>#{</span><span class='kw'>__FILE__</span><span class='rbrace'>}</span><span class='tstring_content'>@</span><span class='embexpr_beg'>#{</span><span class='kw'>__LINE__</span><span class='rbrace'>}</span><span class='tstring_content'>]: \n</span><span class='tstring_end'>&quot;</span></span><span class='op'>+</span>
           <span class='tstring'><span class='tstring_beg'>&quot;</span><span class='tstring_content'>  select_feature_by_score! is the interface for the type of feature weighting algorithms only. \n</span><span class='tstring_end'>&quot;</span></span> <span class='op'>+</span>
           <span class='tstring'><span class='tstring_beg'>&quot;</span><span class='tstring_content'>  please consider select_featue!, \n</span><span class='tstring_end'>&quot;</span></span> <span class='op'>+</span>
@@ -2525,7 +2525,7 @@ <h3>Parameters:</h3>
 </div>
 
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 </div>

diff --git a/doc/FSelector/BaseCFS.html b/doc/FSelector/BaseCFS.html
@@ -239,7 +239,7 @@ <h2>Constructor Details</h2>
 </div>
 
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   0.7.5 (ruby-1.9.3).
 </div>

diff --git a/doc/FSelector/BaseContinuous.html b/doc/FSelector/BaseContinuous.html
@@ -241,7 +241,7 @@ <h2>Constructor Details</h2>
 </div>
 
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diff --git a/doc/FSelector/BaseDiscrete.html b/doc/FSelector/BaseDiscrete.html
@@ -285,7 +285,7 @@ <h2>Constructor Details</h2>
 </div>
 
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   0.7.5 (ruby-1.9.3).
 </div>

diff --git a/doc/FSelector/BaseEnsemble.html b/doc/FSelector/BaseEnsemble.html
@@ -762,7 +762,7 @@ <h3>Parameters:</h3>
 </div>
 
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diff --git a/doc/FSelector/BaseRelief.html b/doc/FSelector/BaseRelief.html
@@ -264,7 +264,7 @@ <h3>Parameters:</h3>
 </div>
 
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diff --git a/doc/FSelector/BaseReliefF.html b/doc/FSelector/BaseReliefF.html
@@ -283,7 +283,7 @@ <h3>Parameters:</h3>
 </div>
 
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diff --git a/doc/FSelector/BetweenWithinClassesSumOfSquare.html b/doc/FSelector/BetweenWithinClassesSumOfSquare.html
@@ -187,7 +187,7 @@ <h2>Constructor Details</h2>
 </div>
 
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diff --git a/doc/FSelector/BiNormalSeparation.html b/doc/FSelector/BiNormalSeparation.html
@@ -202,7 +202,7 @@ <h2>Constructor Details</h2>
 </div>
 
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diff --git a/doc/FSelector/CFS_c.html b/doc/FSelector/CFS_c.html
@@ -181,7 +181,7 @@ <h2>Constructor Details</h2>
 </div>
 
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diff --git a/doc/FSelector/CFS_d.html b/doc/FSelector/CFS_d.html
@@ -201,7 +201,7 @@ <h2>Constructor Details</h2>
 </div>
 
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diff --git a/doc/FSelector/ChiSquaredTest.html b/doc/FSelector/ChiSquaredTest.html
@@ -300,7 +300,7 @@ <h3>Parameters:</h3>
 </div>
 
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diff --git a/doc/FSelector/CorrelationCoefficient.html b/doc/FSelector/CorrelationCoefficient.html
@@ -202,7 +202,7 @@ <h2>Constructor Details</h2>
 </div>
 
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diff --git a/doc/FSelector/DocumentFrequency.html b/doc/FSelector/DocumentFrequency.html
@@ -199,7 +199,7 @@ <h2>Constructor Details</h2>
 </div>
 
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diff --git a/doc/FSelector/EnsembleMultiple.html b/doc/FSelector/EnsembleMultiple.html
@@ -304,7 +304,7 @@ <h3>Parameters:</h3>
 </div>
 
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diff --git a/doc/FSelector/EnsembleSingle.html b/doc/FSelector/EnsembleSingle.html
@@ -343,7 +343,7 @@ <h3>Parameters:</h3>
 </div>
 
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