Mary Abdu

Aktiv seit 2018

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in using partisl least square method to reduce the dimention of the input matrix how to know the inputs that matlab has selected as the important variables, how to select the number of components?
y=outputs; x=inputs; [xl,yl,xs,ys,beta,pctvar]=plsregress(x,y,numberofcomponents)

etwa 7 Jahre vor | 0 Antworten | 0

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what is wrong with the following code, i get the following massege :Subscripted assignment dimension mismatch. Error in Untitled3 (line 14) y2(i)=purelin(y22);
w1=Nx52, b1=Nx1, b2=2x1, w2=2x3 thank you mister madhan, it is look like working with my code (below is the full code) but now ...

etwa 7 Jahre vor | 0

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what is wrong with the following code, i get the following massege :Subscripted assignment dimension mismatch. Error in Untitled3 (line 14) y2(i)=purelin(y22);
w=w*1; load('inputs.mat'); load('outputs.mat'); in=inputs; % loads inputs into variable 'in' t=outputs; ...

etwa 7 Jahre vor | 0

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what is wrong with the following code, i get the following massege :Subscripted assignment dimension mismatch. Error in Untitled3 (line 14) y2(i)=purelin(y22);
thank you; i have already corrected by the foloowing: L=length(a) for i=1:L x=b(:,i); y1=w1*x+b1; y1=tansig(y1)...

etwa 7 Jahre vor | 0

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what is wrong with the following code, i get the following massege :Subscripted assignment dimension mismatch. Error in Untitled3 (line 14) y2(i)=purelin(y22);
clc; clear all; a=[1 2 3; 20 21 22] b=[1 2 3; 4 5 6; 7 8 9] w1=[4 1 5;2 5 0;6 7 10] w2=[10 11 12; 30 1 0] b1=[0.4; 0.2; 0....

etwa 7 Jahre vor | 6 Antworten | 0

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how i can find neural network second output in term of weight and bias, i am using the below code to find the first output
y1=w1*x+b1; y1=tansig(y1); y22=w2*y1+b2; y2=purelin(y22);

etwa 7 Jahre vor | 0 Antworten | 0

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how to rewrite this for feedforward neural network for with 52 inputs and 2 output that predict emission rate not for digits, where i get an error of In an assignment A(:) = B, the number of elements in A and B must be the same. Error in line36
sweep=[3,5:5:50]; %parameter values to test scores=zeros(length(sweep),1); %pre-allcation models=cell(length(sweep),1); %pre-a...

etwa 7 Jahre vor | 2 Antworten | 0

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the following code is to get neural network output in term of weights and biases for one single output how i can rewirte the code for neural network with 2 outputs
i tried with the below code but stil not work could anyone help me please: [r,c]=size(outputs); for i=1:r for j=1:c ...

etwa 7 Jahre vor | 0

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the following code is to get neural network output in term of weights and biases for one single output how i can rewirte the code for neural network with 2 outputs
L=length(outputs); for i=1:L x=inputs(:,i); y1=w1*x+b1; y1=tansig(y1); y22=w2*y1+b2; y2(i)=purelin(y22...

etwa 7 Jahre vor | 1 Antwort | 0

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could any one help me with understanding this code please where w and b are matrices
N=3; w1=[w(1:N);w(N+1:2*N)]'; b1=w(2*N+1:3*N)'; w2=w(3*N:4*N+1); b2=w(end);

etwa 7 Jahre vor | 0 Antworten | 0

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