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Data Mining Lab

 
Author: cui.unige.ch
Category: Data Mining
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You will find here all the material which is relevant for the lab exercises, that is the complete description of the exercises done each time. Information about the used software. In order to have an idea of the material that will be presented in the lab you can take a look at the previous years: Course - 23/10/04, Reminder of basic notions from statistic and introduction to the use of R. Course - 04/11/04, Some more statistical notions, variances and covariances, and introduction to distances. Course - 11/11/04, Introduction to hierarchical clustering, minimum, maximum, average linkage. Course - 18/11/04, Introduction to Self Organised Maps. Course - 25/11/04, Introduction to entropy and information gain. Course - 02/12/04, An introduction to the Weka machine learning environment (version 3.4) Course - 09/12/04, Taking a look on the weka internal library structure Course - 13/01/04, Working with a simple Instance Based Learner. FIRST EXERCISE Course - 20/01/04, Working with a simple Naive Bayes Learner. SECOND EXERCISE Course - 27/01/04, Working with Density Functions. THIRD EXERCISE Course - 27/01/04, Perceptron. FOURTH EXERCISE Course - 15/03/04, Linear Discriminants. FIFTH EXERCISE Course - 22/03/04, Extension of perceptron to Gradient Descent. Course - 22/03/04, Error Estimation Procedures.

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