Questions tagged [model-selection]
Model selection is a problem of judging which model from some set performs best. Popular methods include $R^2$, AIC and BIC criteria, test sets, and cross-validation. To some extent, feature selection is a subproblem of model selection.
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Computing best subset of predictors for linear regression
For the selection of predictors in multivariate linear regression with $p$ suitable predictors, what methods are available to find an 'optimal' subset of the predictors without explicitly testing all $...
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Using information geometry to define distances and volumes…useful?
I came across a large body of literature which advocates using Fisher's Information metric as a natural local metric in the space of probability distributions and then integrating over it to define ...
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Why haven't robust (and resistant) statistics replaced classical techniques?
When solving business problems using data, it's common that at least one key assumption that under-pins classical statistics is invalid. Most of the time, no one bothers to check those assumptions so ...
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What is the interpretation/meaning of confidence intervals in misspecified models?
Consider the following model
$Y_i = f(X_i) + e_i$
from which we observe n iid data points $\left( X_i, Y_i \right)_{i=1}^n$. Suppose that $X_i \in \mathbb{R}^d$ is a $d$ dimensional feature vector. ...
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Incorporating boolean data into analysis
I have a data set of about 3,000 field observations.
The data collected is divided into 20 variables (real numbers), 30 boolean variables, and 10 or so look up variables and one "answer" variable
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Is there any reason to prefer the AIC or BIC over the other?
The AIC and BIC are both methods of assessing model fit penalized for the number of estimated parameters. As I understand it, BIC penalizes models more for free parameters than does AIC. Beyond a ...
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Negative values for AICc (corrected Akaike Information Criterion)
I have calculated AIC and AICc to compare two general linear mixed models; The AICs are positive with model 1 having a lower AIC than model 2. However, the values for AICc are both negative (model 1 ...
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How to choose the number of hidden layers and nodes in a feedforward neural network?
Is there a standard and accepted method for selecting the number of layers, and the number of nodes in each layer, in a feed-forward neural network? I'm interested in automated ways of building neural ...
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