Blog articles tagged 'f#', 'record linkage'

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on 3/27/2013 1:18 PM
Before getting started with Machine Learning in F# Interactive it’s best to prepare it for large datasets and external 64-bit libraries so you don’t get blindsided with strange errors when you happen to cross the line. The good news is it’s a simple proce[...]
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on 9/4/2012 1:52 PM
Levenshtein distance is one of my favorite algorithms. On the surface it seems so very simple, but when you spend some time thinking hard on it deep insights are waiting to be had. The first and most important thing about Levenshtein distance is it’s actu[...]
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on 9/27/2011 6:15 AM
While writing the previous article on tokenized matching I realized I left out some important background information on Jaro-Winkler distance. First, there’s something important to know about the Jaro-Winkler distance: it’s not a metric distance and so do[...]
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on 9/19/2011 1:51 PM
Continuing from last time, let’s look at how one goes from imperative pseudocode to pure functional using Gale-Shapely as an example. Overall, to convert an algorithm from imperative to functional is a fairly simple process once you understand how to conv[...]
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on 9/13/2011 6:00 AM
Initially, one of the biggest problems I found when trying to marry records was the god awful quality of much of data I often have to work with. It’s mostly old mainframe and database data with truncated fields, limited character sets and fields with nons[...]
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