Get flash to fully experience Pearltrees
Table of Contents The client side library plugs into your server side application. The following API allows for you to register users, award points, award badges, and get widgets to render on your website.
That’s quite the mouthful. Let me start with a huge caveat: I’m not an expert on this, and much of it may be incorrect. I studied Bayesian statistics about fifteen years ago in university, but have no recollection of it (that sounds a bit like Bill Clinton: “ I experimented with statistics but didn’t inhale the knowledge ”). Even so, given the increasing quantity of real-time content on the Internet, I find the automated analysis of it fascinating, and hope that something in this post might pique your interest. Naive Bayes classifier Bayesian probability , and in particular the Naïve Bayes classifier , is successfully used in many parts of the web, from IMDB ratings to spam filters.
<img src="http://makezineblog.files.wordpress.com/2011/04/predator.jpg?w=600&h=448" alt="" title="predator" width="600" height="448" class="alignnone size-full wp-image-93249" /> Draw a bounding box around an object in the camera’s field of view and Zdenek Kalal’s open source Predator algorithm will continuously track it in real-time with just a standard webcam. That’s right, get Kinect-like body tracking without the fancy hardware. With all those front-facing cameras out there, just think of the mobile applications!
Position-specific scoring matrices are a popular choice for modelling signals or motifs in biological sequences, both in DNA and protein contexts. A lot of effort has been dedicated to the definition of suitable scores and thresholds for increasing the specificity of the model and the sensitivity of the search. It is quite surprising that, until very recently, little attention has been paid to the actual process of finding the matches of the matrices in a set of sequences, once the score and the threshold have been fixed.
Bayesian classification is an algorithm which allows us to categorize documents probabilistically. I recently started playing with Twitter data and realized there was no Ruby gem which would allow me to build a spam detector for tweets. The classifier gem just works on a set of text by figuring out which words appear in a category but a tweet is much more complicated than that.
By Ilya Grigorik on May 23, 2007 The Family Guy saga continues . A few days ago the editors of the fan site decided to add a new section: favorite quotes. The users responded with enthusiasm, and began submitting hundreds of their favorite gems. Needless to say, the editors were overwhelmed and decided to invite the engineers to pitch in and help sort through the submissions. Of course, after about five minutes of manual labor, the engineers, who were versed in the intricacies of latent semantic indexing and other machine learning techniques, promptly gave up and automated the process - they built a Bayes classifier .