A Lower Bound for Randomized Algebraic Decision Trees.
Dima GrigorievMarek KarpinskiFriedhelm Meyer auf der HeideRoman SmolenskyPublished in: STOC (1996)
Keyphrases
- lower bound
- decision trees
- upper bound
- randomized algorithms
- randomized algorithm
- decision forest
- branch and bound algorithm
- branch and bound
- predictive accuracy
- decision tree induction
- naive bayes
- objective function
- lower and upper bounds
- np hard
- optimal solution
- machine learning
- random forest
- attribute selection
- training set
- machine learning algorithms
- worst case
- constructive induction
- higher order
- decision rules
- feature construction
- decision tree algorithm
- lower bounding
- data mining methods
- special case
- classification rules
- constant factor
- sufficiently accurate
- training data
- competitive ratio
- decision tree learning
- lagrangian relaxation
- vc dimension
- base classifiers