Task, T, with respect to 
performance metric, P, based on experience, E

Training vs. Test Distribution

Attribute-value language (propositional logic)
and generalization/specialization

Bias

Hypotheses space, classification as search, generality structure,
generalisation lattice, version spaces

No free lunch theorem

Conjunctive rules, limits

Measuring performance. Learning/test time, complexity of hypothesis. Evaluation of classification, accuracy, precision, recall, F-measure learning curve, ROC curve

Learning decision trees, entropy, information gain, overfitting, 
pruning

Bayesian learning, idea, naive Bayes classifier

Lazy learning, distance, kNN

SVM, linearilly separable data, kernel trick

Inductive logic programming, generalization/specialization, ILP task,
Generic algorithm, Aleph

Clustering, similarity/distance, single/complete/average, k-Means