MLC
From AIRWiki
Contents
Introduction to the MLC a.k.a. the Machine Learning Curse
- + Machine learning introduction, paradigm, estimation ... [Matt]
Supervised Learning
Good old stuff from stistics
- - logistic regression and linear regression [Bernardo (?)]
- + LDA [Rossella (?) + Simone (?)]
Good old stuf from machine learning
- + Decision trees [Matt]
- ~ Decision rules [Matt + Andrea (?)]
- - Association rules [?]
Statistical approaches
- + Bayesian classifiers [Matt]
Non parametric methods
- - KNN & friends, Locally weighted regression,
Kernel methods
- ~ SVM and Kernel methods [Matt (?) + Luigi (?) + (?)]
Unsupervised Learning
Distributions of data
- + Feature selection and projection (PCA, ICA, ...) [Rossella (?)+ Simone]
Clustering
- + Clustering galore [Davide (?)]
Graphical models
- ~ Bayesian networks [Matt + Luigi (?)]
Non Parametric techniques
- Kernel based density estimation, ... [Rossella (?) + Luigi (?) + Simone]
Time Varying Models
- + Markov Chains [Matt + Bernardo (?) +Simone]
- + Hidden Markov Models [Matt + Simone (?)]
- - Dynamic Bayesian Networks
Learning Techniques and Methodologies
- ~ Cross-Validation, Bootstrapping, and model evaluation [Matt (?)]
- - Adaboost, boosting and bagging ... [?]
Knowledge representation and Learning
- - ontologies ...
Text analysis and learning
- - text analysis, classification, relevance feedback, latent semantic [Ahmed]
Image analysis and learning
- - Image analysis and learning
