Sigmoid Function

replaced Tanh with Sigmoid for the activation function

ELMclassifier.m

@@ -58,7 +58,7 @@
 bias  = rand(nUnits,1);
 
 % compute hidden neuron output matrix H
-H = tanhActFun(W1*trX + repmat(bias,[1,nPatternsTr]));
+H = sigActFun(W1*trX + repmat(bias,[1,nPatternsTr]));
 
 % compute hidden->output weights W2
 Hinv = pinv(H');
@@ -70,7 +70,7 @@
 trYhat   = temp';
 
 % ...  and validation dataset
-Hval     = tanhActFun(W1*valX + repmat(bias,[1,nPatternsVal]));
+Hval     = sigActFun(W1*valX + repmat(bias,[1,nPatternsVal]));
 temp     = (Hval' * W2)';
 [~,temp] = max(temp,[],1);
 valYhat  = temp';

sigActFun.m

@@ -0,0 +1,31 @@
+function y = sigActFun(x)
+% sigmoid activation function for ELM
+%
+%
+%
+% 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.
+%
+%
+% This file is part of Matlab-Multi-objective-Feature-Selection.
+% 
+%     Matlab-Multi-objective-Feature-Selection is free software: you can redistribute 
+%     it and/or modify it under the terms of the GNU General Public License 
+%     as published by the Free Software Foundation, either version 3 of the 
+%     License, or (at your option) any later version.     
+% 
+%     This code is distributed in the hope that it will be useful,
+%     but WITHOUT ANY WARRANTY; without even the implied warranty of
+%     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+%     GNU General Public License for more details.
+% 
+%     You should have received a copy of the GNU General Public License
+%     along with MATLAB_IterativeInputSelection.  
+%     If not, see <http://www.gnu.org/licenses/>.
+%
+
+y = 1./(1+exp(-x));