# Questions tagged [mean-squared-error]

For questions related to the mean squared error (MSE) function, which is often used to solve regression problems.

25 questions
Filter by
Sorted by
Tagged with
21 views

### Loss function not able to capture the maxima of probability distribution

I am trying to predict noise (random gaussian) with the help of a neural network. I am implementing a L2 loss (torch.nn.function.mse_loss) for computing the loss function between the prediction ...
171 views

### Does MSE loss function work in NN training for predicting values between 0-1?

In a NN regression problem, considering that MSE is squaring the error and the error is between 0 and 1 would it be pointless to use MSE as our loss function during model training? For example: ...
40 views

### Which mathematical properties do PSNR and MSE hold?

We know the Structural Similarity Index (SSIM) holds the following properties: Unique maximum: S(x, y) = 1 if and only if x = y Boundedness: ...
18 views

### Is there any different evaluation metrics(Performance Metrics) for Deep learning ,Machine, learning and NLP?

I'm a little confused about machine learning. I know we can use accuracy, and precision-recall when it comes to a classification problem, and when it comes to regression problems, we usually go with ...
47 views

### Multi-layer network only predicts linear trends

I have made a neural network from scratch (in java), which is refusing to switch out of linear regression. I have pushed up the layer sizes (it now has 2 hidden layers, both with 5 neurons), and yet ...
5k views

### In variational autoencoders, why do people use MSE for the loss?

In VAEs, we try to maximize the ELBO = $\mathbb{E}_q [\log\ p(x|z)] + D_{KL}(q(z \mid x), p(z))$, but I see that many implement the first term as the MSE of the image and its reconstruction. Here's a ...
363 views

### "Porpoising" in latter stages of validation loss and MSE charts in Keras

Performing a prediction of a continuous y target using Keras, the simple structure of the code revolves around; ...
143 views

### What error should I use for RNN?

I'm relatively new to machine learning, and I don't know what error I should use for an RNN. I want to use a simple Elman RNN to predict the cases of Covid-19 there will be in a hospital for the next ...
586 views

### Would either $L_1$ or $L_2$ regularisation lower the MSE on the training and test data?

Consider linear regression. The mean squared error (MSE) is 120.5 for the training dataset. We've reached the minimum for the training data. Is it possible that by applying Lasso (L1 regularization) ...
1 vote
229 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 (...
278 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 ...
176 views

### What is the definition of a loss function in the context of neural networks?

I have read what the loss function is, but I am not sure if I have understood it. For each neuron in the output layer, the loss function is usually equal to the square of the difference value of the ...
1k 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
184 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 ...
897 views

...
1 vote
117 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 ...
94 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 ...
9k 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 ...