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Questions tagged [mse]

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

233 questions
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Why CNN model cannot fit well for a pair of random tensor?

I build a toy CNN model to fit a pair of random tensors(input_tensor & truth). batch_size = 1 channel = 3 input_size = 128 input_tensor = torch.rand((batch_size, channel, input_size, input_size)) truth = torch.rand((batch_size, channel, input_size,…
ojipadeson
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why does the mse loss had a sudden jump?

i'm working on a regression problem using neural network. the mse loss would decrease at the beginning of train and the accuracy is satisfactory, yet, when the train process goes on, the loss had a huge jump, and maintain at a certain value,like the…
sing a song
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Dataframe with scipy minimize function

Im trying to minimize sum square function that works with a dataframe. The df is as follows: ds = pd.DataFrame({'t': [*np.linspace(0,300,7)], 'Ca': [0.05, 0.038, 0.0306, 0.0256, 0.0222, 0.0195, 0.0174]}) My model that Im using with sum square…
Nilon
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ModuleNotFoundError: No module named 'sewar.full_ref'; 'sewar' is not a package

I installed Sewar using pip install sewar after that i got same error like below from sewar.full_ref import mse, rmse, psnr, uqi, ssim, ergas, scc, rase, sam, msssim, vifp import cv2 org = cv2.imread("org_path") blur =…
Parthiban Marimuthu
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Scikit Learn DecisionTreeRegressor algorithm not consistent

I am currently using decision trees (using Scikit Learn DecisionTreeRegressor) to fit Regression tree. The problem I'm facing is that using the algorithm with same data as 6 months ago there is a slight change in output (ie. the optimal split…
vasilis polimenis
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MSE Loss is reducing with a very small amount during training pytorch

I'm trying out my first deep learning program for speech separation using ideal ratio mask. It is a BLSTM model. The mse loss obtained while training is reducing with a very small quantity. Any idea about why it is happening and how to fix it??…
Soni
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Flattening the input to nn.MSELoss()

Here's the screenshot of a YouTube video implementing the Loss function from the YOLOv1 original research paper. What I don't understand is the need for torch.Flatten() while passing the input to self.mse(), which, in fact, is nn.MSELoss() The…
Aarush Aggarwal
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How is MSE calculated for multi-output regression in keras?

I have a Keras deep learning model that outputs 6 variables. model = Sequential() model.add(Dense(32, input_dim=12, kernel_initializer='he_uniform', activation='relu')) model.add(Dense(256, activation='relu')) model.add(Dense(32,…
Glen Hamblin
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Why does the best score from gridsearch and score from the model with the best parameters differ?

I am using Grid search with predefined split. I want to choose the best hyperparameters for my model based on MSE score on validation dataset. Here is my code: data = pd.read_csv('data/concrete.csv').astype(float) X =…
dmasny99
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Create custom convolutional Loss function that only takes parts of the tensor

I have a convolutional network that gets images, but also a colored border on each image for additional information input to the network. Now I want to calculate the loss, but the usual loss function will also take the predicted border into account.…
Pia Lüdemann
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How implement a Mean Standard Error (MSE) metric for NNI (Neural network intelligence) in pytorch?

I am somewhat new to pytorch since I have been using Keras for some years. Now I want to run a network architecture search (NAS) based on DARTS: Differentiable Architecture Search (see https://nni.readthedocs.io/en/stable/NAS/DARTS.html) and it is…
pittnerf
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Keras Custom loss Penalize more when actual and prediction are on opposite sides of Zero

I'm training a model to predict percentage change in prices. Both MSE and RMSE are giving me up to 99% accuracy but when I check how often both actual and prediction are pointing in the same direction ((actual >0 and pred > 0) or (actual < 0 and…
iKey
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MSE of the validation (and test) sets from repeated k-Fold on Ridge regression?

TLDR Probably this problem but how can we do it using sklearn? I'm okay if only the mean over the CVs I did for each lambda or alpha are shown in the plots. Hi all, if I understand correctly, we need to cross-validate on the training set to select…
Yuki.F
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Abnormal increase in loss after 75 epochs (Using MSE and Binary Crossentropy)

I have trained a tensorflow.keras model over the night and was suprised about the training process (please see the attached picture). Can anyone tell me, what can produce such an effect during training? I have trained with mse (right) and one other…
Romaxx
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How the MSE loss calculated for multiple neurons in output layer

i have a feedforward regression network (in Keras with TensorFlow backend) with single hidden layer (30 neurons) and output layer with 2 neurons (for Imaginary and Real parts of complex signal) ...My question is how the MSE loss is calculated…
igorek
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