All Questions
Tagged with uncertainty prediction-interval
17 questions
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Confidence and prediciton intervals for power law fit
I would like to determine confidence intervals and prediction intervals for a noisy dataset that follows a power law distribution.
I have a dataset that (to my eye) follows power law behavior in the ...
1
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0
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228
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Probabilistic machine learning models: parameter uncertainty
Consider models such as DeepAR, ngboost and other frameworks to the general problem of predicting the parameters of some parametric distribution with some black-box function, call it f(X). The ...
- 831
3
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1
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609
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How to represent the interval or uncertainty on regression predictions in an 'experimental vs predicted' plot?
Using an example similar to the one from R predict, simulate some independent variable ($x$) data, map them to an observed ...
- 751
2
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1
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215
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Bootstrapping (aleatoric and epistemic) risk score uncertainty
I am working on various risk score estimation problems. I assume individual subjects are associated with a true risk
$$r_i = f(x_i; \epsilon_i), \quad 0 \leq r_i \leq 1,$$
where $x_i$ is some ...
- 3,088
5
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1
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355
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Risk score uncertainty quantification
I am working on various risk score estimation problems. I assume individual subjects are associated with a true risk
$$ r_i = f(x_i, \varepsilon)$$
where $x_i$ is some available information about the ...
- 3,088
0
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1
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60
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Uncertainity band in Neural networks
I am working on a problem where I have to give the uncertainty band of my predictions like the image attached.
I have seen a StackExchange solution for this, but in the solution code, we are using ...
1
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1
answer
280
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How to calculate uncertainty for predictions coming from cascade of models?
I have developed a bunch of models to predict house prices. It is a 3 fold process:
I fit a gbm (first_model) and get the first prediction (first_pred),
there are some sub-models (simple lineer ...
- 219
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1
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46
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Likelihood that a prediction falls above (below) 110% (90%) of the prediction
For my client I have to predict some products' prices with gbm (scikit). So in the production, I am to give prediction intervals. That is, I need to provide how likely a real price falls above 110% or ...
- 219
2
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1
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107
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Accounting for multiple layers of uncertainty in a model
Let's say I have data on 10 stores that sell widgets, each of which received num_orders number of orders in a certain timeframe, and sold a total of ...
- 669
6
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1
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1k
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Bootstrap intervals for predictions, how to interpret it?
I want to come up with a way to get how confident I am in my predictions. I am not using a Bayesian model so I was thinking a bootstrap confidence interval would be good:
I would re-sample my ...
- 1,373
13
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2
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11k
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Predicting Uncertainty in Random Forest Regression [duplicate]
Scenario: I'm trying to build a random forest regressor to accelerate probing a large phase space. I'm using python/scikit-learn to perform the regression, and I'm able to obtain a model that has a ...
- 131
4
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1
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2k
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How to incorporate uncertainty of actual historical data into forecast prediction intervals?
I wonder how we can incorporate uncertainty of the actual historical data into forecast prediction intervals. In other words, we would have for example 95% range instead of the data points for ...
- 95
6
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1
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484
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Is chaining neural networks in this way a good way to estimate a prediction interval?
Suppose you want to predict the outcome of some real valued function $f$. The details of the function are unknowable and it also has a stochastic component. You identify some variables $\theta$ which ...
- 1,275
2
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0
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109
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Obtaining uncertainties from an errors-in-variables machine learning algorithm
In my field, every value reported comes with a 1-sigma uncertainty value.
I'm using random forest regressors to estimate a value. All of my inputs have 1-sigma uncertainty information with them.
...
- 3,132
12
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2k
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Empirical Prediction interval for time series forecast based on quantile regression
As Gardner notes "almost all point forecasts are wrong", so prediction intervals (PI) are necessary to quantify uncertainty and help us make informed decisions. There exists theoretical PI, and in ...
- 8,655
9
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2
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2k
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Does it make sense to generate prediction intervals for the estimates of a logistic regression?
Say I have a binary outcome of 0 or 1 and suppose I were to use logistic regression model to estimate the probability a new sample will have an outcome of 1.
I have read answers (for example here: ...
- 361
1
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1
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163
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Regression confidence on new data point
I'm in the process of building a prediction system, and one of its requirements is to be able to give the confidence of a prediction. That is, given a set of independent variables, it should be able ...
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