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How does the number of hidden neurons affect the output?



Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern)
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsHow to fight underfitting in a deep neural netNeural Network Hidden Neuron Selection StrategyImportance of Random initialisation VS number of hidden unitsWhy does my Multilayer Perceptron only classify linearly?Cost/loss functions for multi-tasking regression neural networksCan a single-layer ANN get XOR wrong?Ensemble models - neural network input both original data and predictions of other models?Is a Neural Network with 20 times the number of input neurons (on hidden layers) guaranteed to overfit? When is this not so?Calculating sin function with neural network using pythonWhat does the “Loss” value given by Keras mean?










1












$begingroup$


I'm currently creating neural networks within MatLab, and I was wondering how does the number of hidden neurons affect the output? There is 1 hidden layer only on both. I did two tests on the same data, one with 5 neurons, and one with 10 neurons. The test with 5 neurons had a smaller Mean Square Error, however, the MSE was the smallest at epoch 4, whereas, in the one with 10 neurons, the Mean Square Error was larger, however, the MSE was smallest at epoch 3.



I was wondering of an explanation for this, and I thought that since there is more neurons in the test with 10 neurons, it is able to process/learn data faster, which explains the smaller epoch, however, the larger amount of neurons means that data isn't processed in as much detail as it would be with 5 neurons, which increases the Mean Square Error, and it would be the opposite of this for the 5 neurons.



Can anyone tell me if i'm on the right track at all with that explanation? I'm completely new to AI in general, so excuse me if I got anything completely wrong.










share|improve this question









$endgroup$







  • 1




    $begingroup$
    Did MSE on Validation set show similar results ?
    $endgroup$
    – Shamit Verma
    Apr 4 at 10:44










  • $begingroup$
    can you please give exact numbers of MSEs?
    $endgroup$
    – Preet
    Apr 4 at 12:16










  • $begingroup$
    @Preet sure, 5 neurons: 0.13201, smallest MSE at epoch 4, 10 neurons: 0.14386, smallest MSE at epoch 3
    $endgroup$
    – Kappa123
    Apr 4 at 22:35















1












$begingroup$


I'm currently creating neural networks within MatLab, and I was wondering how does the number of hidden neurons affect the output? There is 1 hidden layer only on both. I did two tests on the same data, one with 5 neurons, and one with 10 neurons. The test with 5 neurons had a smaller Mean Square Error, however, the MSE was the smallest at epoch 4, whereas, in the one with 10 neurons, the Mean Square Error was larger, however, the MSE was smallest at epoch 3.



I was wondering of an explanation for this, and I thought that since there is more neurons in the test with 10 neurons, it is able to process/learn data faster, which explains the smaller epoch, however, the larger amount of neurons means that data isn't processed in as much detail as it would be with 5 neurons, which increases the Mean Square Error, and it would be the opposite of this for the 5 neurons.



Can anyone tell me if i'm on the right track at all with that explanation? I'm completely new to AI in general, so excuse me if I got anything completely wrong.










share|improve this question









$endgroup$







  • 1




    $begingroup$
    Did MSE on Validation set show similar results ?
    $endgroup$
    – Shamit Verma
    Apr 4 at 10:44










  • $begingroup$
    can you please give exact numbers of MSEs?
    $endgroup$
    – Preet
    Apr 4 at 12:16










  • $begingroup$
    @Preet sure, 5 neurons: 0.13201, smallest MSE at epoch 4, 10 neurons: 0.14386, smallest MSE at epoch 3
    $endgroup$
    – Kappa123
    Apr 4 at 22:35













1












1








1





$begingroup$


I'm currently creating neural networks within MatLab, and I was wondering how does the number of hidden neurons affect the output? There is 1 hidden layer only on both. I did two tests on the same data, one with 5 neurons, and one with 10 neurons. The test with 5 neurons had a smaller Mean Square Error, however, the MSE was the smallest at epoch 4, whereas, in the one with 10 neurons, the Mean Square Error was larger, however, the MSE was smallest at epoch 3.



I was wondering of an explanation for this, and I thought that since there is more neurons in the test with 10 neurons, it is able to process/learn data faster, which explains the smaller epoch, however, the larger amount of neurons means that data isn't processed in as much detail as it would be with 5 neurons, which increases the Mean Square Error, and it would be the opposite of this for the 5 neurons.



Can anyone tell me if i'm on the right track at all with that explanation? I'm completely new to AI in general, so excuse me if I got anything completely wrong.










share|improve this question









$endgroup$




I'm currently creating neural networks within MatLab, and I was wondering how does the number of hidden neurons affect the output? There is 1 hidden layer only on both. I did two tests on the same data, one with 5 neurons, and one with 10 neurons. The test with 5 neurons had a smaller Mean Square Error, however, the MSE was the smallest at epoch 4, whereas, in the one with 10 neurons, the Mean Square Error was larger, however, the MSE was smallest at epoch 3.



I was wondering of an explanation for this, and I thought that since there is more neurons in the test with 10 neurons, it is able to process/learn data faster, which explains the smaller epoch, however, the larger amount of neurons means that data isn't processed in as much detail as it would be with 5 neurons, which increases the Mean Square Error, and it would be the opposite of this for the 5 neurons.



Can anyone tell me if i'm on the right track at all with that explanation? I'm completely new to AI in general, so excuse me if I got anything completely wrong.







neural-network






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Apr 4 at 10:28









Kappa123Kappa123

62




62







  • 1




    $begingroup$
    Did MSE on Validation set show similar results ?
    $endgroup$
    – Shamit Verma
    Apr 4 at 10:44










  • $begingroup$
    can you please give exact numbers of MSEs?
    $endgroup$
    – Preet
    Apr 4 at 12:16










  • $begingroup$
    @Preet sure, 5 neurons: 0.13201, smallest MSE at epoch 4, 10 neurons: 0.14386, smallest MSE at epoch 3
    $endgroup$
    – Kappa123
    Apr 4 at 22:35












  • 1




    $begingroup$
    Did MSE on Validation set show similar results ?
    $endgroup$
    – Shamit Verma
    Apr 4 at 10:44










  • $begingroup$
    can you please give exact numbers of MSEs?
    $endgroup$
    – Preet
    Apr 4 at 12:16










  • $begingroup$
    @Preet sure, 5 neurons: 0.13201, smallest MSE at epoch 4, 10 neurons: 0.14386, smallest MSE at epoch 3
    $endgroup$
    – Kappa123
    Apr 4 at 22:35







1




1




$begingroup$
Did MSE on Validation set show similar results ?
$endgroup$
– Shamit Verma
Apr 4 at 10:44




$begingroup$
Did MSE on Validation set show similar results ?
$endgroup$
– Shamit Verma
Apr 4 at 10:44












$begingroup$
can you please give exact numbers of MSEs?
$endgroup$
– Preet
Apr 4 at 12:16




$begingroup$
can you please give exact numbers of MSEs?
$endgroup$
– Preet
Apr 4 at 12:16












$begingroup$
@Preet sure, 5 neurons: 0.13201, smallest MSE at epoch 4, 10 neurons: 0.14386, smallest MSE at epoch 3
$endgroup$
– Kappa123
Apr 4 at 22:35




$begingroup$
@Preet sure, 5 neurons: 0.13201, smallest MSE at epoch 4, 10 neurons: 0.14386, smallest MSE at epoch 3
$endgroup$
– Kappa123
Apr 4 at 22:35










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