Update readme.txt

readme.txt

@@ -1,36 +1,31 @@
-This toolbox implements the WQEISS/WMOSS/FQEISS feature selection techniques 
-for classification problems presented in Karakaya et al. (2015).
+This toolbox implements the WQEISS/WMOSS/FQEISS feature selection techniques for classification problems presented in Karakaya et al. (2015).
 
-Currently only the NSGA-II algorithm (Deb et al., 2002) is supported, but additional scripts 
-for the Borg version(Hadka and Reed, 2012) will be uploaded shortly. 
+Currently only the NSGA-II algorithm (Deb et al., 2002) is supported, but additional scripts  for the Borg version(Hadka and Reed, 2012) will be uploaded shortly. 
 
-This toolbox depends on the following contributions which have to be
-donwloaded and referenced. 
+This toolbox depends on the following contributions which have to be donwloaded and referenced. 
 
 1) Song Lin's NGPM toolbox for NSGA-II, 
-      http://in.mathworks.com/matlabcentral/fileexchange/31166-ngpm-a-nsga-ii-program-in-matlab-v1-4
+   http://in.mathworks.com/matlabcentral/fileexchange/31166-ngpm-a-nsga-ii-program-in-matlab-v1-4
 
-2)  Hanchuan Peng's Mutual Information computation toolbox
-      http://www.mathworks.com/matlabcentral/fileexchange/14888-mutual-information-computation
+2) Hanchuan Peng's Mutual Information computation toolbox
+  http://www.mathworks.com/matlabcentral/fileexchange/14888-mutual-information-computation
 
-3)  Yi Cao's Pareto-front toolbox
-      http://www.mathworks.com/matlabcentral/fileexchange/17251-pareto-front
-
-The workings of the NSGA-II version of the algorithms are illustrated in "script_example_NSGAII.m"
-for the "Heart" dataset of the UCI Repository (Lichman, 2013). 
+3)Yi Cao's Pareto-front toolbox
+  http://www.mathworks.com/matlabcentral/fileexchange/17251-pareto-front
 
+The NSGA-II version of the algorithms is illustrated in "script_example_NSGAII.m" for the "Heart" dataset of the UCI Repository (Lichman, 2013). 
 
 
 
 References: 
 
 Deb, K., Pratap, A., Agarwal, S., Meyarivan, T., 2002. 
 A Fast and Elitist Multiobjective Genetic Algorithm. 
-IEEE Trans. Evol. Comput. 6, 182�197. doi:10.1109/4235.996017
+IEEE Trans. Evol. Comput. 6, 182–197. doi:10.1109/4235.996017
 
 Hadka, D., Reed, P., 2012. 
 Borg: An Auto-Adaptive Many-Objective Evolutionary Computing Framework. 
-Evol. Comput. 21, 1�30. doi:10.1162/EVCO_a_00075
+Evol. Comput. 21, 1–30. doi:10.1162/EVCO_a_00075
 
 Lichman, M. (2013). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. 
 Irvine, CA: University of California, School of Information and Computer Science.
@@ -42,12 +37,7 @@ IEEE Trans. Cybern. doi:10.1109/TCYB.2015.2444435
 
 
 
-Copyright 2015 Riccardo Taormina (riccardo_taormina@sutd.edu.sg), 
-     Gulsah Karakaya (gulsahkilickarakaya@gmail.com;), 
-     Stefano Galelli (stefano_galelli@sutd.edu.sg),
-     and Selin Damla Ahipasaoglu (ahipasaoglu@sutd.edu.sg;. 
-
-Please refer to README.txt for further information.
+Copyright 2015 Riccardo Taormina (riccardo_taormina@sutd.edu.sg), Gulsah Karakaya (gulsahkilickarakaya@gmail.com;), Stefano Galelli (stefano_galelli@sutd.edu.sg), and Selin Damla Ahipasaoglu (ahipasaoglu@sutd.edu.sg;. 
 
 
 This file is part of Matlab-Multi-objective-Feature-Selection.