% hObject    handle to Etah (see GCBO)% eventdata  reserved - to be defined in a future version of MATLAB% handles    empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.%       See ISPC and COMPUTER.if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))    set(hObject,'BackgroundColor','white');endfunction Etay_Callback(hObject, eventdata, handles)% hObject    handle to Etay (see GCBO)% eventdata  reserved - to be defined in a future version of MATLAB% handles    structure with handles and user data (see GUIDATA)% Hints: get(hObject,'String') returns contents of Etay as text%        str2double(get(hObject,'String')) returns contents of Etay as a doubleinput = str2num(get(hObject,'String')); %checks to see if input is empty. if so, default input1_editText to zeroif (isempty(input))     set(hObject,'String','0')endguidata(hObject, handles);% --- Executes during object creation, after setting all properties.function Etay_CreateFcn(hObject, eventdata, handles)% hObject    handle to Etay (see GCBO)% eventdata  reserved - to be defined in a future version of MATLAB% handles    empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.%       See ISPC and COMPUTER.if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))    set(hObject,'BackgroundColor','white');endfunction MSE_lim_Callback(hObject, eventdata, handles)% hObject    handle to MSE_lim (see GCBO)% eventdata  reserved - to be defined in a future version of MATLAB% handles    structure with handles and user data (see GUIDATA)% Hints: get(hObject,'String') returns contents of MSE_lim as text%        str2double(get(hObject,'String')) returns contents of MSE_lim as a doubleinput = str2num(get(hObject,'String'));iris_data.dat %checks to see if input is empty. if so, default input1_editText to zeroif (isempty(input))iris_data.dat     set(hObject,'String','0')endguidata(hObject, handles);% --- Executes during object creation, after setting all properties.function MSE_lim_CreateFcn(hObject, eventdata, handles)% hObject    handle to MSE_lim (see GCBO)% eventdata  reserved - to be defined in a future version of MATLAB% handles    empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.%       See ISPC and COMPUTER.if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))    set(hObject,'BackgroundColor','white');end%% --- Executes on button press in Classify.function Classify_Callback(hObject, eventdata, handles)% hObject    handle to Classify (see GCBO)% eventdata  reserved - to be defined in a future version of MATLAB% handles    structure with handles and user data (see GUIDATA)set1_ir = str2num(get(handles.set1_LR,'String')) ;set1_ur = str2num(get(handles.set1_UR,'String'));set2_ir = str2num(get(handles.set2_LR,'String'));set2_ur = str2num(get(handles.set2_UR,'String'));set3_ir = str2num(get(handles.set3_LR,'String'));set3_ur = str2num(get(handles.set3_UR,'String'));set1_ir2 = str2num(get(handles.set1_LR_td,'String'));set1_ur2 = str2num(get(handles.set1_UR_td,'String'));set2_ir2 = str2num(get(handles.set2_LR_td,'String'));set2_ur2 = str2num(get(handles.set2_UR_td,'String'));set3_ir2 = str2num(get(handles.set3_LR_td,'String'));set3_ur2 = str2num(get(handles.set3_UR_td,'String'));in_ir = str2num(get(handles.Input_LR,'String'));in_ur = str2num(get(handles.Input_UR,'String'));out_ir = str2num(get(handles.Output_LR,'String'));out_ur = str2num(get(handles.Output_UR,'String'));L = str2num(get(handles.Hidden_Nodes,'String'));etay = str2num(get(handles.Etay,'String'));etah = str2num(get(handles.Etah,'String'));MSE_thr = str2num(get(handles.MSE_lim,'String'));%load iris_data.dat;    %Incorporate din UI%a= iris_data;global aDim = size(a);p = (in_ur-in_ir) + 2 ; %number of input + biasm = (out_ur-out_ir) + 1 ;  % no. of output% Training data setD11=a(set1_ir:set1_ur,in_ir:in_ur);D12=a(set2_ir:set2_ur,in_ir:in_ur);D13=a(set3_ir:set3_ur,in_ir:in_ur);Np = (in_ur-in_ir) + 1 ; % No. of inputs excluding biasD1=[D11; D12 ;D13] ;     % Training data set (INPUT)Dim2 = size(D1);X11=a(set1_ir:set1_ur,out_ir:out_ur);X12=a(set2_ir:set2_ur,out_ir:out_ur);X13=a(set3_ir:set3_ur,out_ir:out_ur);X1=[X11; X12 ;X13]/10;  % Training data set (Normalised OUTPUT) Dim3 = size(X1);% Normalising Inputpmin=min(D1);pmax=max(D1);for i=1:Dim2(1)             d1(i,:)=D1(i,:)-pmin;end;x=(0.9-0.1)./(pmax-pmin);for i=1:Np    pin(:,i)=x(i)*d1(:,i)+0.1;end%N=Dim2(1);X= [pin'; ones(1,N)];   % add bias input 1Wh = 0.25*randn(L-1,p)/p;Wy = 0.25*randn(m,L)/L;MSE=10.0;       %Initialise some random value but greater than test aim valuewhile(MSE>=MSE_thr)    H = ones(L-1,N)./(1+exp(-Wh*X));    % f(net)    Hp = H.*(1-H);                      % f_prime(net) hidden        H=[H;ones(1,N)];                    % add bias 1     Y = tanh(Wy*H);                     % output = fj(netj)(semilinear activation function)    Yp=1-Y.^2;                          % f_prime(net) output        Ey = X1' - Y;                       % error in output    JJ = (sum((Ey.*Ey)'))';    MSE = sum(JJ)/(N*Dim3(2))           %#ok<NOPTS> % Mean square error in output         delY = Ey.*Yp;                      % error*f_prime(net)    dWy = delY*H';                      % Gradient output layer weight        Eh = Wy(:,1:L-1)'*delY;             % error in output from hidden layer              delH=Eh.*Hp;    dWh = delH*X';                      % Gradient output layer weight        Wy= Wy + etay*dWy;                    % Output layer weight correction        Wh = Wh + etah*dWh;                   % Hidden layer weight correction    end dataTrain(3,3) = 0; % classify for p = 1:N     for i = 1:3         if X1(p)*10 == i             for j = 1:3                 if round(Y(p)*10) == j                     dataTrain(i,j) = dataTrain(i,j)+1;                     break                 end             end            end     end end % Testing of ModelD21=a(set1_ir2:set1_ur2,in_ir:in_ur);        % Test InputD22=a(set2_ir2:set2_ur2,in_ir:in_ur);D23=a(set3_ir2:set3_ur2,in_ir:in_ur);D2=[D21; D22 ;D23];X21=a(set1_ir2:set1_ur2,out_ir:out_ur);          % Test outputX22=a(set2_ir2:set2_ur2,out_ir:out_ur);X23=a(set3_ir2:set3_ur2,out_ir:out_ur);X2=[X21; X22 ;X23];Dim = size(D2);N=Dim(1);% Normalising Test Inputpmin=min(D2);pmax=max(D2);for i=1:N             d2(i,:)=D2(i,:)-pmin;end;x=(0.9-0.1)./(pmax-pmin);for i=1:Np    pin2(:,i)=x(i)*d2(:,i)+0.1;endX= [pin2'; ones(1,N)];   % add bias input 1H = ones(L-1,N)./(1+exp(-Wh*X));H=[H;ones(1,N)];                    % add bias 1 Y2 = tanh(Wy*H);  dataTest(3,3) = 0; % classify for p = 1:N     for i = 1:3         if X2(p) == i             for j = 1:3                 if round(Y2(p)*10) == j                     dataTest(i,j) = dataTest(i,j)+1;                     break                 end             end            end     end endc = num2str(dataTrain(1,1));set(handles.tr11,'String',c);guidata(hObject, handles);c = num2str(dataTrain(1,2));set(handles.tr12,'String',c);guidata(hObject, handles);c = num2str(dataTrain(1,3));set(handles.tr13,'String',c);guidata(hObject, handles);c = num2str(dataTrain(2,1));set(handles.tr21,'String',c);guidata(hObject, handles);c = num2str(dataTrain(2,2));set(handles.tr22,'String',c);guidata(hObject, handles);c = num2str(dataTrain(2,3));set(handles.tr23,'String',c);guidata(hObject, handles);c = num2str(dataTrain(3,1));set(handles.tr31,'String',c);guidata(hObject, handles);c = num2str(dataTrain(3,2));set(handles.tr32,'String',c);guidata(hObject, handles);c = num2str(dataTrain(3,3));set(handles.tr33,'String',c);guidata(hObject, handles);c = num2str(dataTest(1,1));set(handles.tt11,'String',c);guidata(hObject, handles);c = num2str(dataTest(1,2));set(handles.tt12,'String',c);guidata(hObject, handles);c = num2str(dataTest(1,3));set(handles.tt13,'String',c);guidata(hObject, handles);c = num2str(dataTest(2,1));set(handles.tt21,'String',c);guidata(hObject, handles);c = num2str(dataTest(2,2));set(handles.tt22,'String',c);guidata(hObject, handles);c = num2str(dataTest(2,3));set(handles.tt23,'String',c);guidata(hObject, handles);c = num2str(dataTest(3,1));set(handles.tr31,'String',c);guidata(hObject, handles);c = num2str(dataTest(3,2));set(handles.tt32,'String',c);guidata(hObject, handles);c = num2str(dataTest(3,3));set(handles.tt33,'String',c);guidata(hObject, handles);% --- If Enable == 'on', executes on mouse press in 5 pixel border.% --- Otherwise, executes on mouse press in 5 pixel border or over text4.function text4_ButtonDownFcn(hObject, eventdata, handles)% hObject    handle to text4 (see GCBO)% eventdata  reserved - to be defined in a future version of MATLAB% handles    structure with handles and user data (see GUIDATA)