Learning k-Testable tree sets from positive data
نویسنده
چکیده
A k-Testable tree set in the Strict sense (k-TS) is essentially defined by a finite set of patterns of "size" k that are permitted to appear in the trees of the tree language. Given a positive sample S of trees over a ranked alphabet, an algorithm is proposed which obtains the smallest k-TS tree set containing S. The proposed algorithm is polynomial on the size of S and identifies the class of k-TS tree languages in the limit from positive data.
منابع مشابه
MMDT: Multi-Objective Memetic Rule Learning from Decision Tree
In this article, a Multi-Objective Memetic Algorithm (MA) for rule learning is proposed. Prediction accuracy and interpretation are two measures that conflict with each other. In this approach, we consider accuracy and interpretation of rules sets. Additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. This...
متن کاملInformation extraction from structured documents using k-testable tree automaton inference
Information extraction (IE) addresses the problem of extracting specific information from a collection of documents. Much of the previous work on IE from structured documents, such as HTML or XML, uses learning techniques that are based on strings, such as finite automata induction. These methods do not exploit the tree structure of the documents. A natural way to do this is to induce tree auto...
متن کاملA probabilistic extension of locally testable tree languages
Probabilistic k-testable models (usually known as k-gram models in the case of strings) can be easily identified from samples and allow for smoothing techniques to deal with unseen events. In this paper we introduce the family of stochastic k-testable tree languages and describe how these models can approximate any stochastic rational tree language. This is applied, as a particular case, to the...
متن کاملLearning Concatenations of Locally Testable Languages from Positive Data
This paper introduces the class of concatenations of locally testable languages and its subclasses, and presents some results on the learnability of the classes from positive data. We rst establish several relationships among the language classes introduced, and give a su cient condition for a concatenation operation to preserve nite elasticity of a language class C. Then we show that, for each...
متن کاملLearning k-Testable and k-Piecewise Testable Languages from Positive Data
The families of locally testable (LT ) and piecewise testable (PWT ) languages have been deeply studied in formal language theory. They have in common that the role played by the segments of length k of their words in the first family is played in the second by their subwords (sequences of non necessarily consecutive symbols), also of length k. We propose algorithms that, given k > 0, identify ...
متن کاملذخیره 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 1993