# Questions tagged [mse]

MSE stands for mean-squared error. It's a measurement of an empirical loss in certain mathematical models, especially regression models.

42 questions
Filter by
Sorted by
Tagged with
45 views

### Predict actual result after model trained with MinMaxScaler LinearRegression

I'm sorry I'm new to modeling and still learning, I was doing the modeling on the House Pricing dataset. My target is to get the mse result and predict with the input variable I have done the modeling,...
30 views

### Proof for MSE = Var + Bias2

I am trying to prove the equality of $$\rm MSE=Var+Bias^2$$ but obviously I got something wrong as they don't equal in my calculation: So here is the example. I use monte carlo to estimate this ...
• 133
55 views

### MAE vs MSE for linear regression

Several articles says that MAE is robust to outliers but MSE is not and MSE can hamper the model if errors are too huge. My question is that MSE and MAE both are error matrices,our priority is to just ...
10 views

### Do I need to rescale input labels before training (label values between 20..51)?

I'm trying to build model for this datatset (Age prediction): The input image has the shape: 3, 128, 128 and the predicted labels (ages) range between 20 to 51. I ...
• 317
10 views

### Trying to implement a loss function read from a journal-article in python

Computer science undergrad here. I am trying to understand Eqn 12 from this paper so that I can implement it in python code. In this paper, the NN model takes a blurred image as input and outputs a ...
1 vote
99 views

### how to calculate loss function?

i hope you are doing well , i want to ask a question regarding loss function in a neural network i know that the loss function is calculated for each data point in the training set , and then the ...
• 23
32 views

### Why does log-transforming the target have a huge impact on MSE value?

I am doing linear regression using the Boston Housing data set, and the effect of applying $\log(y)$ has a huge impact on the MSE. Failing to do it gives MSE=34.94 ...
• 109
33 views

### Batch Size influences R2 score a lot, but not MSE (much)

If I train a model following a random search, (and in general for this problem I am working on), a big batch size seems to control R2 score where bs=200 or more, say, roughly, gives R2 scores of 0.95 ...
• 71
43 views

### What causes explosion in MSE when training?

I (probably) well overfitted/overtrained a model. But I was just curious as to what might cause this type of behaviour. I carried on training (Epoch 1/50 is not the first epoch of training this model)....
• 71
22 views

### weighted mse - weights as function of time

I am predicting timeseries data using LSTM (in tensorflow). Currently I am using MSE as my metric of choice. I would like to create my own custom Weighted MSE metric, such that the weights are a ...
10 views

### Increasing (negative) R2 coincident with decreasing (positive) MSE during hyper parameter optimisation

I have a densely connected NN and I'm running a hyper parameter optimisation for multi-target output. During hyper parameter optimisation training, each epoch KerasTuner focuses on val_loss. During ...
• 71
12 views

### How to extract MSEP or RMSEP from lassoCV?

I'm doing lasso and ridge regression in R with the package chemometrics. With ridgeCV it is easy to extract the SEP and MSEP values by ...
1 vote
65 views

### Can't understand an MSE loss function in a paper

I'm reading a paper published in nips 2021. There's a part in it that is confusing: This loss term is the mean squared error of the normalized feature vectors and can be written as what follows: ...
16 views

### Appropriate loss function and metrics for regression task with mixed outputs

I'm trying to train an EfficientNet-based Keras model that takes an image as input and returns two numeric values as output. Here's the model: ...
• 111