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Cascade-forward neural network adding new units
As answered in your previous post. Despite the name, these are different networks. Hope this helps. Greg

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Cascade-forward neural network
You are right. Despite the name, these are not the same network. Greg

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How to refine a feedforward neural network after train?
My previous post shows the assumption that combining TRAIN and ADAPT is a guarantee for success is not necessarily a good one. ...

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Improve accuracy of small data set using Neural Network
[I N ] = input; % [ 4 24 ] [O N ] = target;% [ 1 24 ] Ntrn = N -2*round(0.15N) % 16 default Ntrneq = Ntrn*O ...

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What is data in regression plot in neural network?
The circles are your OUTPUT data. HOWEVR, You have 3 classes of target the plots only show outputs of 0 and 1. Where are the...

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Neural Network for finding characteristic points in data
You need N pairs of I-dimensional inputs and corresponding O-dimensional targets contained in 2 matrices [ I N ] = size(inpu...

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How could I cancel pre-processing and post-processing stages when training a neural network?
To remove mapminmax as a processFcn but still keep removeconstantrows close all, clear all, clc % WITH DEFAULT MAPMINMA...

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Neural Networks - Can I constrain the range of the output of the network?
You probably only need 1 hidden node. Scale the output from 0 to 1 and use a logsig output function. Hope this helps ...

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Neural Network Time Series tool
NARNET is the function for a single series help NARNET doc NARNET Search BOTH NEWSGROUP and ANSWERS with greg NARNE...

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The test of normality for resiuals of a neural network
Original comment by dpb on 30 Sep 2016 at 20:38 upgraded to an ANSWER: That the model residuals aren't normally distributed....

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Neural Network problem with the goal
For difficult problems, success beyond the default parameter values typically depends on the number of hidden nodes and choice o...

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how to apply DATA to inputs in neural network MLP?
Data must consist of N pairs: I-dimensional "I"nputs in an I x N matrix and a corresponding O x N "O"utput target mat...

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I have a mse mistake in Neural Network
You are confused. The task is to find a local minimum that is sufficiently low. I use the goal mse(target-output) <= 0.01...

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Implementation of neural network equation
The N I-dimensional "I"nputs are normalized from x to xn The N O-dimensional "O"utput targets are normalized from t to tn ...

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how to compare the characteristics of two graphs
After looking at the graphs, I would 1. Compare means 2. Compare variances and standard deviations. 3. Compare standard...

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Function approximation: Neural network great 'on paper' but when simulated results are very bad?
AN OPTIMISTIC ESTIMATE USING DIVIDETRAIN: % Solve an Input-Output Fitting problem with a Neural Network % Scrip...

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NARX test set closed loop
You seem confused: 1. OL trn, val and tst subsets are automatically tested by TRAIN. 2. The OL configuration is then...

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Confusion matrix neural network plot interpretation
By default, the data is divided into three subsets (trn/val/tst): total = training + validation + testing You can think of...

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Confusion matrix neural network plot interpretation
This is a VERY POOR classification confusion matrix layout 1. There should be three confusion matrices a. One 5x5 count ...

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Which classifier (SVM or Neural Networks) is accurate for fault detection in Power Systems?
N pairs of I-dimensional "I"nputs and corresponding O-dimensional "O"utput targets in two matrices: [ I N ] = size(input) ...

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Which classifier (SVM or Neural Networks) is accurate for fault detection in Power Systems?
It depends on which one you are most comfortable wth. *Thank you for formally accepting my answer* Greg

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i want to optimize a neural network parameters by genetic algorithm and i get below code from matlab support, but the result is very poor even for a very simple function. how can i improve the result and is there any better code for my porpuse?
http://www.mathworks.com/matlabcentral/newsreader/view_thread/344888#944621 If you can improve the code please let me know. ...

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How to differentiate between Mse(training) and Mse(testing) ??
In order to obtain the break down of mse into its trn/val/tst parts you have to obtain the training record, tr from training; ...

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myself Dhandapani, can i know how to write the trained neural network properties to a text file. so that i can use the text file to create the new network easily
save net Hope this helps. *Thank you for formally accepting my answer* Greg

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How to improve the performance of my neural network
The code you posted is too complicated for your first time out. See the examples in the documentation using the commands hel...

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Pattern Recognition Training Model
In general, data for neural nets are N PAIRS of I-dimensional "I"nputs and O-dimensional "O"utput targets. the size of the matri...

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NARXnet with Multi input
> My first question is, am I do it right in finding the ID and FD for multi-input? In general yes. However there are correcti...

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Getting Target Data from Given Input Matrix Neural Networks
N pairs of I-dimensional "I"nput vectors and corresponding O-dimensional "O"utput target vectors stored in matrices input and ta...

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How to get the transfer function equation for the implemented neural network
I misplaced my turban and crystal ball. Therefore I cannot tell you where you have gone wrong. OH! It just occurred to me! ...

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effect by splitting data in training neural network
Sorry, my first answer, though interesting, does not directly address your basic problem. 1. Distributions are well represe...

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