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The answer is "yes," there is lots one can do with sparse data. This response is far from "complete" but will review a few options in a kind of "DIY" shotgun listing.
In other words, it is up to the analyst to decide which option may be appropriate to pursue. The first consideration is to identify where the sparsity is occurring, e. Wrt sparse or rare events in the target variable, e. The mistake is this: This means that with sparse or rare event data, logistic regression will produce biased results.
Commonly recommended "solutions" for this problem are to go out and get a larger sample of data or, alternatively, to specifically subsample those segments that are both important to the analysis and sparsely populated. This is a bad idea for at least two reasons: Better solutions are possible: Gary King, Harvard political scientist and statistical methodologist, discusses rare event analysis Quantification and prediction of extreme events in a one-dimensional nonlinear dispersive wave model Consider healthcare or hospital data where a combination such as male patients given a diagnostic code of "pregnancy" is possible from a purely computational point of view in terms of cross-classifying a set of features, but males actually giving birth is impossible, i.
But sex and gender are different constructs. So, until transgender patients e. As noted, sparsely populated features are different, requiring special tools to facilitate analysis from those employed for target variables.
The following is a "laundry list" or shotgun set of options for dealing with sparse features. Much of it was gathered by simply browsing for the keywords "inference from sparse data.
Adopt a Bayesian modeling framework. Frequentists might object to this claim. MCMC sampling provides a workaround for sparsely populated categorical features in that pooling data across the sampling iterations builds a distribution about a feature in the posterior, even in cases where there is a sample size of 1.
Gelman, in his blog, also discusses sparsity here Using Big Data to study rare eventsHere are the top 25 Thesis Student profiles on LinkedIn. Get all the articles, experts, jobs, and insights you need.
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