MLC

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Revision as of 09:56, 26 January 2009 by AhmedGhozia (Talk | contribs)

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Supervised


  • + Machine learning introduction, paradigm, estimation ... [Matt]
Distributions of data
  • + Feature selection and projection (PCA, LDA, ICA, ...) [Rossella (?)+ Simone]
Linear & other
  • - Good old stuff: logistic regression, linear regression [Bernardo (?)]
  • + LDA
Rules
  • + Decision trees [Matt]
  • ~ Decision rules [Matt + Andrea (?)]
  • - Association rules [?]
Bayes
  • + Bayesian classifiers [Matt]
Non parametric methods
  • - KNN & friends, Locally weighted regression,
...?

~ SVM and Kernel methods [Matt (?) + Luigi (?) + (?)]

Statistical Learning & Unsupervised


Graphical models
  • + Markov Chains [Matt + Bernardo (?) +Simone]
  • ~ Bayesian networks [Matt + Luigi (?)]
  • (Dynamic Bayesian Networks) + Hidden Markov Models [Matt + Simone (?)]
Expectation & maximization
  • Kernel based density estimation, ... [Rossella (?) + Luigi (?) + Simone]
  • Clustering

Knowledge representation


  • - ontologies ...

Text analysis


  • - text analysis, classification, relevance feedback, latent semantic [Ahmed]

Image analysis

Unmapped:

  • - Adaboost, boosting and bagging ... [?]
  • ~ Cross-Validation, Bootstrapping, and model evaluation [Matt (?)]
  • + Clustering galore [Davide (?)]

indexing, ...