Questions tagged [statistical-ai]

For questions about the applications/clarifications/intuitions/proofs behind the use of statistical methods in AI/ML programs.

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Simplification of expected reward under the limit in continuous tasks

I was reading the average reward setting for continuous tasks from rich sutton's book (page 202, 2nd edition). There he perform a simplification over the expected reward under the limit approaching to ...
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40 views

Is maximum likelihood estimation meaningless for a dataset of only outliers?

From my understanding, maximum likelihood estimation chooses the set of parameters for the estimator that maximizes likelihood with the ground truth distribution. I always interpreted it as the ...
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0answers
13 views

Mapping given probabilities to empirical probabilities

Consider following problem statement: You have given $n$ actions. You can perform any of them. Each action gives you success with some probability. The challenge is to perform given finite number of ...
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48 views

How to calculate the data noise variance for a prediction interval?

I have a neural network that connects $N$ input variables to $M$ output variables (qoi). By default, neural networks just give out point estimations. Now, I want to plot some of the quantity of ...
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1answer
31 views

When a linear discriminant could give excellent or possibly even the optimal classification accurcy?

I am actually reading the linear classification. There is a question in the question set behind the chapter in the book as follows: Sketch two multimodal distributions for which a linear discriminant ...
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25 views

Do the variance and bias belong to the policy or value functions?

Recently, I read many papers on variance and bias. But I am still confused by the two notions, the variance or bias belongs to who? Policy or value? If the variance or bias is large or low, what ...
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27 views

What is the difference between an generalised estimating equation and a recurrent neural network?

What is the difference between a generalised estimating equation (GEE) model and a recurrent neural network (RNN) model, in terms of what these two models are doing? Apart from the differences in the ...
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21 views

Keras correlation coefficient as network metric in R

does anyone know how to use the correlation coefficient or squared correlation coefficient as a metric in keras in R (although other languages may provide clues). This is for a CNN that functions ...
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81 views

Confidence interval around a DNN prediction

I am facing a problem and do not know whether it is even solvable: I want to predict the behaviour of a system using a DNN, say a CNN, in the sense that I want to predict the time and intensity of a ...
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19 views

Methods in training models to minimize distance between statistical summaries of data and samples from model, to get a better approximation function

Introduction: A big problem with deep learning methods involving neural networks is that they tend to do really poorly outside the boundaries of the approximation it has learned from the data it is ...
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26 views

How can I find the correlation between the input and output of a neural network?

I'm trying to get a value for a correlation between a function input and its output. One brute force way to get this is to sample the entire space and find the standard deviation of the resulting ...
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83 views

How to build naive bayes graph from data

For an university assignment I have to use the HuginLite software to do some probabilistic inferences with different algorithms. One of these algorithms is Naive Bayes but its graph is not built ...