Papers and More on Data Mining
April 22, 2011 7:15 PM Subscribe
posted by JoeXIII007 (14 comments total)
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It has applications in health care
, facial recognition
, economics/related areas
, and of course, much much more
. Previously, MeFi discussed controversial homeland security applications
, and the nexus between social networking and mobile devices
that further contributes to the pool. With plenty to dig into
, let's talk Data Mining
in more detail.
First, some High School Primer on AI
previously shown on MeFi.
Second, and more important, introductions to key concepts:
- Dimension Reduction: Principle Components Analysis and, for distance (not just geographical) based dimension reduction, Multidimensional Scaling. Algorithms and methods that take multivariate datasets and attempt to find a what's most important/influential within a dataset.
- Classification: Linear / Quadratic / Bayesian Quadratic Discriminant Analysis (LDA, QDA, BQDA). Add some paper on PCA vs. LDA. The Naive Bayes Classifier for a 'feature' based approach. Lastly, but certainly not leastly, Support Vector Machines.
- Clustering: when you have no labels, make them, with, for example, K-means Clustering.
To complete this, a good book on the topic: Pattern Recognition and Machine Learning by Chris M. Bishop