A Lower Bound for Randomized Algebraic Decision Trees
Dima GrigorievMarek KarpinskiFriedhelm Meyer auf der HeideRoman SmolenskyPublished in: Electron. Colloquium Comput. Complex. (1995)
Keyphrases
- lower bound
- decision trees
- randomized algorithms
- upper bound
- randomized algorithm
- decision forest
- decision tree induction
- lower and upper bounds
- branch and bound
- branch and bound algorithm
- optimal solution
- decision rules
- rule induction
- random forest
- naive bayes
- worst case
- machine learning
- lower bounding
- objective function
- predictive accuracy
- boosted decision trees
- constant factor
- random forests
- sufficiently accurate
- decision tree algorithm
- upper and lower bounds
- higher order
- training data
- data mining methods
- decision tree learning
- classification rules
- machine learning algorithms
- polynomial approximation
- lagrangian relaxation
- nearest neighbour
- linear programming relaxation
- sample complexity
- learning algorithm