Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [heuristic]

A heuristic is a general rule for making some sort of decision or judgement. Pioneering work in the study of heuristics was done by Amos Tversky and Daniel Kahneman.

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Should I use the Kernel Trick whenever possible for non-linear data?

I recently learned about the use of the Kernel trick, which maps data into higher dimensional spaces in an attempt to linearize the data in those dimensions. Are there any cases where I should avoid using this technique? Is it just a matter of…
JDong
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Is it better to select distributions based on theory, fit or something else?

This is bordering on a philosophical question, but I am interested in how others with more experience think about distribution selection. In some cases it seems clear that theory might work best (mice tail lengths are probably normally distributed).…
HFBrowning
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Why can't we trust our intuition with probability?

If ever there was a case where this become clear is with the Monty Hall problem. Even the great Paul Erdos got fooled by this problem. My question which may be difficult to answer is what is it about probability that we can be so confident of an…
Michael R. Chernick
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Why does the L2 norm heuristic work in measuring uniformity of probability distributions?

To start off, please go through this question regarding measuring non-uniformity in probability distributions. Among several good answers, user495285 has suggested a heuristic of simply taking the L2 norm of a vector whose values add to 1. I've…
Ketan
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How does Bayesian analysis make accurate predictions using subjectively chosen probabilities?

Since Kahneman and Tversky found that humans do not accurately assume probabilities, how can Bayes theorem use subjectively chosen probabilities to accurately predict things (like insurance policies), when given extra data? In other words, humans…
Grubbmeister
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Is machine learning an heuristic method?

I'm asking this out of curiosity. In the past I have thought of an heuristic as a "quick and dirty" rule not based on data analysis, as opposed to a solution which uses machine learning or statistical models. For example imagine I have the following…
Giacomo
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What Are Shrinking Heuristics

I have been working on a project with LibSVM and have noticed there is an option to train the SVM model with "shrinking heuristics" which are used to speed up the classifier training. After doing some googling, I couldn't find anything substantial…
eNc
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Heuristics streaming data matching

I have an index composed by thousands of documents. Slightly modified copies of those documents are sent to my application in small chunks, and I need to check, from those chunks, which document has is being transmitted. All documents are sent to my…
Felipe Martins Melo
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Conditions for Poisson approximation of the superposition of non-Poisson processes

It is well known that the superposition of $N$ Poisson processes is itself a Poisson process with an intensity given by $\sum_{n=1}^{N} \lambda _{n}$. Conversely a superposition including any non-Poisson component processes is not Poisson. However,…
dylan2106
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Hill Climbing with hysteresis

I'm trying to solve a specific problem related to my work in experimental physics. However, I'll try to keep my question as general as possible so that it is useful to a wider audience. If some context would be useful to clarify things, please…
user129412
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What is a sensible way to truncate data to a region that fits a model?

I want to use an exponential decay model in python to relate the flow rate in a device to the mass left inside it, in particular $flow=a−b×e^{−c×mass}$ where a, b and c are the parameters of the model. Here are some of my measurements together with…
st210
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Finding the maximum of a function $f(x)$ without analytically evaluating $f'(x)$

I'm an experimental physicist, trying to automate a relatively simple (but sensitive) optimization in my measurements that is currently done completely manually and takes up a lot of my time. I figure that machine learning should have ample tools…
user129412
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What is the right name for "heuristics" with guaranteed improvement?

I am working on an algorithm which tries to improve existing predictive model. The predictive model is associated with several objectives (such as accuracy or model size) that can be optimized. Let's say that the algorithm is guaranteed to improve…
tomas
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Maximizing Variance in Samples

I have a given set of numbers and I want to divide it into even n subsets, maximising the sum of each subset's variance. Can I do this better than creating each subset with random sampling?
Torkoal
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Optimizing while collecting data - optimization in a real world problem

I want to conduct a soil analysis using a different mix of let says Nutrition A, Nutrition B and Nutrition C. Since I can put for each nutrition multiple values, I cannot try out all the possible combinations. I am therefore looking for a simple…
JohnAndrews
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