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entrepreneurship, rich internet applications, software architecture, agile development, ai, and more feb 23, 2013 intro to mathematics in similarity classifiers part 2 intro this article will provide an introduction to the mathematics of similarity classifiers, specifically jaccard, extended jaccard, and cosine. we will attempt to introduce the topics in layman's terms and provide examples that readers can play with and watch the results. while this intro series of articles will go into theory and formulas full of greek letters, they will first build upon simple explanations and real world examples. hopefully in reading this article you can gain an understanding of both the application and the math involved. the example for the first set of classifiers i'm stealing an example from the great book "programming collective intelligence" by toby segaran. but rather than focus on the code, this article will use the example to simplify and explain the math. the premise is that a store like amazon.com wants to recommend items a customer might like. in order to make a decision on what to recommend we can take two different approaches. we could find similar movie buyers, and recommend movies that those similar buyers like. this is akin to getting movie recommendations from a friend who has similar tastes as you. alternatively, we could try to classify how similar movies are to each other, and recommend similar movies to the movies that you already like. for example, one could argue batman is similar to superman because both are superhero movies, so we could recommend batman to buyers who purchase superman. for brevity this article is going to stick with only talking about the similarity of movie viewers rather than item similarity, but the algorithms are the same. click the link below to play with a simple app that calculates the similarity between movie viewers using the mathematics we will discuss in detail. read more >> posted by jeff plummer at saturday, february 23, 2013 16 comments: labels: machine learning , similarity classifiers jan 21, 2013 introduction to the math behind similarity classifiers – part 1 abstract this article provides an introduction to the world of similarity classifiers in a way that is simple and fun. we will attempt to introduce the topics in laymen's terms and provide examples that readers can play with and watch the results. while this intro series of articles will go into theory and formulas full of greek letters, they will first build upon simple explanations and real world examples. hopefully in reading this article you can gain an understanding of both the application and the math involved. introduction to similarity classifiers similarity-based classifiers estimate the similarity between *things*. once we know things are similar, we can begin to group them and make decisions based on that grouping. commercial businesses can make more money knowing that people who buy one type of item, are very often interested in "similar" items. doctors who can successfully treat a specific pathology with specific medications can often successfully treat "similar" patients with those same medications. and the list goes on and on. pandora: "is this song similar to 'linkin park' such that we ought to group it with the ‘link park’ radio station?" google news: "is this unknown web article similar to these other top news articles such that we ought to group them together in our news aggregator?" amazon: "is the movie 'speed 2' similar to the movie 'cinderella' and we should recommend it as a purchase to 'speed 2' buyers?" image organizer: "is this image similar to these other images in a collection, and thus we think this new image is of the same person?" read more >> posted by jeff plummer at monday, january 21, 2013 21 comments: labels: machine learning , similarity classifiers jul 11, 2012 arraycollection ‘source’ attribute vs listcollectionview ‘list’ attribute i recently stumbled upon an interesting problem that highlighted the difference between arraycollection ‘source’ attribute and the listcollection ‘list’ attribute. i was working through some code that was not paying close attention to how it re-wrapped collection data. in some cases a collection was created to wrap the ‘source’ of another collection as in figure 1. in other cases a new collection was created to wrap the ‘list’ of the original collection as in figure 2. the code was wrapping the data in new arraycollections in order to apply different sorting and filtering, which is an extremely common use for collection views, but was stumbling upon some interesting runtime results… not all of the collection views were updating with the collection changes. var ac1 : arraycollection = new arraycollection ( ) ; var ac2 : arraycollection = new arraycollection ( ac1 . source ) ; figure 1 – clone arraycollection using the ‘source’ attribute var ac1 : arraycollection = new arraycollection ( ) ; var ac2 : arraycollection = new arraycollection ( ) ; ac2 . list = ac1 . list ; figure 2 – clone arraycollection using the ‘list’ attribute how ‘source’ and ‘list’ relate and why it matters jumping into the flex sdk source code the setter method arraycollection.source creates a new arraylist around the original source to create the ‘list’ attribute of the new collection view. what this means is that depending on how your new collection view wraps the original data, you may end up with the same source, but different lists (see figure 3 below). figure 3 – possible relationships in related arraycollections read more >> posted by jeff plummer at wednesday, july 11, 2012 17 comments: labels: adobe flex , apache flex jul 10, 2012 why doesn't tweetmeme work anymore? ??? switching to twitter's own re-tweet button because tweetmeme doesn't work with blogspot anymore. posted by jeff plummer at tuesday, july 10, 2012 22 comments: feb 1, 2012 unit tests as a measure of code cleanliness i recently attended the 2011 adobe max conference and sat in on the unit testing adobe flex session by michael labriola of digital primates. i expected the session to be a repeat of what i already know and strongly believe. unit tests simplify testing, document your code, improve maintainability, blah blah blah. the aspect of the lecture that i found most fascinating was on writing clean code and using unit tests as a means to verify code cleanliness. my training regarding unit tests has been pretty informal. through experience i’ve found that when i write automated tests my bug count goes way down, and when i do have a bug i have a great starting point to isolate and fix issues. i’ve always understood the difference between unit, integration, and functional testing but never much cared because all 3 have the benefits mentioned above. the simple discovery, however, that being able to unit test your code in the strictest sense is a very good measurement as to the cleanliness of your code was pretty eye-opening. if your code base is only testable at the integration level, your code is probably too tightly coupled and does not have good encapsulation. read more >> posted by jeff plummer at wednesday, february 01, 2012 24 comments: labels: adobe flex , clean code , unit testing sep 13, 2011 a simple and effective agile process introduction whenever i hear other software leads complain about their waterfall-ish development process, i always ask why haven’t they tried something more agile. the most common answer i’ve heard back is that they don’t know where to begin. entire books are written on the subject of agile development, and it’s a pretty big sell to project management that you want drop everything and try something that seemingly requires chapters to describe. that type of change tends to make project management cringe. the truth is books are written about agile development because people want to make money selling books about agile development. agile development is phenomenally simple and you make mod
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