Questions tagged [uncertainty]

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Using conformal predictors to estimate uncertainty?

I read this interesting book on conformal predictors: Conformal predictors are a way to choose a set that's guaranteed to include the true labels with some pre-chosen ...
user151434's user avatar
1 vote
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Model uncertainty quantification

I'm reading a paper about model uncertainty quantification. Specifically, it says epistemic uncertainty is a kind of uncertainty due to lack of knowledge about a particular region in the input space. ...
piero's user avatar
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What is the best way to combine cross-validation and bootstrapping for one application?

We intend to model data with non-parametric covariate splines and we would like to understand the uncertainty of the parameter estimates/response estimates. Currently, we use cross-validation to model ...
Stan Tendijck's user avatar
1 vote
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Is there a way to quantify uncertainty in classification?

I'm thinking of a way to build an extension to a binary classifier (actually I will get the output probabilities like in logistic regression, so technically you should call this regression) that ...
Tom's user avatar
  • 65
1 vote
1 answer

Can a simple distance to a few nearest data points be used a measure of the uncertainty of a prediction?

One of the 'selling points' of the Gaussian process regression is that it provides not only the model but also the uncertainty estimate of a prediction. Then usually a picture is shown with a curve ...
Vladislav Gladkikh's user avatar
1 vote
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How to forecast time series with negative trend in test set and big uncertainty? (uncertainty due to Covid and Ukraine crisis)

Recently I started to create a machine learning model for a European customer for around 800 product time series. The goal is to produce a monthly forecast for the 6 months ahead. Since this customer ...
LGe's user avatar
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Some questions about Ensemble batch prediction intervals (EnbPI) algorithm

On line 18, should j not start with t-s+1 and end with t? On line 19 why is the same x_t considered in the loop?
user1156715's user avatar
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Convert Regression output to classification based on prospective performance of model

Let’s say I have a regression model that predicts experimental value in the range of 4 to 8 of an object based on a set of features. I am aiming to design an oBject with an experimental value of great ...
ChemDev's user avatar
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Adressing uncertainty of a spatio-temporal multivariate timeseries with random temporal gaps

Imagine there are multiple locations of interest from where water samples are gathered manually. Each sample is immediately analyzed, converted to a numerical value (a real number) and fed into a ...
Laurimann's user avatar
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1 answer

Is it ok to use MC-dropout technique to estimate uncertainty without putting dropout after every weight layer?

In the paper by Kendall and Gal (What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?), dropout is being set after every convolutional layer. However, is it still legit to ...
tMan27's user avatar
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uncertainties in non-convex optimization problems (neural networks)

How do you treat statistical uncertainties coming from non-convex optimization problems? More specifically, suppose you have a neural network. It is well known that the loss is not convex; the ...
Dave's user avatar
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How can I distribute samples optimally to fit a model?

I'm trying to fit a model to a low number (~5-10) of data points. I might be able to suggest the optimal distribution of the data points beforehand, knowing a bit about the data and the model I ...
Matthias's user avatar
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