MLC

Supervised

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• + 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

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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

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• - ontologies ...

Text analisys

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• - text analysis, classification, relevance feedback, latent semantic

Unmapped:

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

• + Clustering galore [Davide (?)]

indexing, ...