Learning
Supervised Learning
- Methodology: N-fold cross-validation; induction of decision trees, entropy, information gain, ID3, C4.5, overfitting, ensembles of classifiers, bagging, boosting, scaleup, complete classification vs nuggets, feature selection: LOOCV, racing, schemas; inductive logic programming, FOIL, minimum description length, Grendel
Reinforcement Learning
- Cummulative discounted reward, dynamic programming, policy iteration, value iteration, temporal-difference learning