Questions tagged [mean-squared-error]
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11
questions
1
vote
1answer
28 views
How do I prove that the MSE is zero when all predictions are equal to the corresponding labels?
In the back-propogation algorithm, the error term is:
$$
E=\frac{1}{2}\sum_k(\hat{y}_k - y_k)^2,
$$
where $\hat{y}_k$ is a vector of outputs from the network, $y_k$ is the vector of correct labels (...
0
votes
1answer
61 views
What is the meaning of these equations in Noise2Noise paper?
I am trying to understand what is meant by following equations in the Noise2Noise paper by Nvidia.
What is meant by the equation in this image? What is $\mathbb{E}_y\{y\}$? And how should I try to ...
3
votes
2answers
117 views
What is the advantage of using cross entropy loss & softmax?
I am trying to do the standard MNIST dataset image recognition test with a standard feed forward NN, but my network failed pretty badly. Now I have debugged it quite a lot and found & fixed some ...
1
vote
0answers
33 views
How can a learning rate that is too large cause the output of the network (and the error) to go to infinity?
It happened to my neural network, when I use a learning rate of <0.2 everything works fine, but when I try something above 0.4 I start getting "nan" errors because the output of my ...
2
votes
1answer
76 views
1
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0answers
44 views
How MSE should be appliead with multi target deep network?
I'm having a problem understanding how the MSE should be used when working with a multidimensional target, e.g 3 dimensiones. (My outputs are continuois values, not categorical)
Let us say I have a ...
2
votes
2answers
50 views
What does it mean if classification error is equal between two networks but the MSE is different?
I'm experimenting with training a feedforward neural network using a genetic algorithm and I've done a few tests using both the mean squared error and classification error functions as fitness ...
3
votes
0answers
121 views
How to implement Mean square error loss function in mini batch GD
I have a vectorized implementation of the neural network in c++. I successfully solve the classification problems of Fashion MNIST and CIFAR.
Now I am modifying my code to do the Linear regression. I ...
2
votes
4answers
87 views
Is it normal to have the root mean squared error greater on the test dataset than on the training dataset?
I am new to deep learning.
I am training a model and I am getting a root mean squared error (RMSE) greater on the test dataset than on the training dataset.
What could be the reason behind this? Is ...
2
votes
2answers
67 views
How to determine the target value when using ReLU as activation function?
Consider the following simple neural network with only one neuron.
The input is $x_1$ and $y_2$, where $-250 < x < 250$ and $-250 < y < 250$
The weights of the only neuron are $w_1$ and $...
3
votes
2answers
1k views
In which cases is the categorical cross-entropy better than the mean squared error?
In my code, I usually use the mean squared error (MSE), but the TensorFlow tutorials always use the categorical cross-entropy (CCE). Is the CCE loss function better than MSE? Or is it better only in ...
