# What is the error histogram in neural network matlab?

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I asked yesterday, but I don't understand. because I used neural network matlab tool first time

So I ask you again

1. error values don't have to minus value??

2. What is the y axis? is it the number of traning, validation and test data set?

3. why the highest bar exist? is it mean highst bar has 0.001502 error values?

4. what is zero error? I don't understand zero error line means. it means 0? it means distribution which bar close 0?

Is it best performance??? what does mean in this graph??

I'm sorry for many questions.. Thank you in advance.

##### 1 Comment

Aasma aslam
on 3 Apr 2021

### Answers (2)

Sourav Bairagya
on 10 Dec 2019

Error histogram is the histogram of the errors between target values and predicted values after training a feedforward neural network. As these error values indicates how predicted values are differing from the target values, hence these can be negative.

Bins are the number of vertical bars you are observing on the graph. The total error range is divided into 30 smaller bins here.

Y-axis represents the number of samples from your dataset, which lies in a particular bin. For example, at the mid of your plot, you have a bin corresponding to the error of 0.001502 and the height of that bin for training dataset lies below but near to 150 and validation and test dataset lies between 150 and 200. It means that many samples samples from you different datasets have an error lies in that following range.

Zero error line corresponding to the zero error value on the error axis (i.e. X-axis). In this case zero error point falls under the bin with centre 0.001502.

To get more details you can leverage this link:

##### 0 Comments

usha chintalapati
on 15 May 2020

Can you please explain this plot?

##### 1 Comment

Mohit Nair
on 13 May 2021

Error histogram is the histogram of the errors between target values and predicted values after training a feedforward neural network. As these error values indicates how predicted values are differing from the target values, hence these can be negative.

Bins are the number of vertical bars you are observing on the graph. The total error range is divided into 20 smaller bins here.

Y-axis represents the number of samples from your dataset, which lies in a particular bin. For example, at the mid of your plot, you have a bin corresponding to the error of -0.04225 to 0.04225 and the height of that bin for training dataset lies below but near to 40 and validation and test dataset lies between 50 and 60. It means that many samples samples from you different datasets have an error lies in that following range.

Zero error line corresponding to the zero error value on the error axis (i.e. X-axis). In this case zero error point falls under the bin with centre 0.04225.

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