Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables

نویسندگان

  • Igor Chikalov
  • Shahid Hussain
  • Mikhail Ju. Moshkov
چکیده

In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization of decision trees and decision rules) to conduct experiments. We show that, for each monotone Boolean function with at most five variables, there exists a totally optimal decision tree which is optimal with respect to both depth and number of nodes. c © 2013 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of KES International.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Dynamic Programming Approach for Study of Decision Trees

In the presentation, we consider extensions of dynamic programming approach to the study of decision trees as algorithms for problem solving, as a way for knowledge extraction and representation, and as classifiers which, for a new object given by values of conditional attributes, define a value of the decision attribute. These extensions allow us (i) to describe the set of optimal decision tre...

متن کامل

Testing Properties of Boolean Functions

Given oracle access to some boolean function f, how many queries do we need to test whether f is linear? Or monotone? Or whether its output is completely determined by a small number of the input variables? This thesis studies these and related questions in the framework of property testing introduced by Rubinfeld and Sudan (’96). The results of this thesis are grouped into three main lines of ...

متن کامل

Function Evaluation Via Linear Programming in the Priced Information Model

Wedetermine the complexity of evaluatingmonotone Boolean functions in a variant of the decision tree model introduced in [Charikar et al. 2002]. In thismodel, reading different variables can incur different costs, and competitive analysis is employed to evaluate the performance of the algorithms. It is known that for a monotone Boolean function f, the size of the largest certificate, aka PROOF ...

متن کامل

Exact Learning Boolean Function via the Monotone Theory

We study the learnability of boolean functions from membership and equivalence queries. We develop the Monotone Theory that proves 1) Any boolean function is learnable in polynomial time in its minimal DNF size, its minimal CNF size and the number of variables n. In particular, 2) Decision trees are learnable. Our algorithms are in the model of exact learning with membership queries and unrestr...

متن کامل

Learning Monotone Functions from Random Examples in Polynomial Time

We give an algorithm that learns any monotone Boolean function f : {−1, 1}n → {−1, 1}to any constant accuracy, under the uniform distribution, in time polynomial in n and in thedecision tree size of f. This is the first algorithm that can learn arbitrary monotone Booleanfunctions to high accuracy, using random examples only, in time polynomial in a reasonablemeasure of the c...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013