Decision tree is one of the most widely used and practical methods in data mining and machine learning discipline. However, many discretization algorithms developed in this field focus on univariate only, which is inadequate to handle the critical problems especially owned by medical domain. In this paper, we propose a new multivariate discretization method called Multivariate Interdependent Di...

Two critical bottle necks in mining frequent tree patterns from tree databases are the exponential number of mined patterns and the lack of user focus on the mining process. We propose, in this paper, an algorithm that solves the problems for unordered attribute trees by mining only the compact representation of tree patterns, i.e. closed tree patterns, and allows users to mine only trees of th...

Decision tree methods generally suppose that the number of categories of the attribute to be predicted is fixed. Breiman et al., with their Twoing criterion in CART, considered gathering the categories of the predicted attribute into two superclasses. In this paper, we propose an extension of this method. We try to merge the categories in an optimal unspecified number of superclasses. Our metho...

In this paper we address the problem of multiobjective attribute selection in data mining. We propose a multiobjective genetic algorithm (GA) based on the wrapper approach to discover the best subset of attributes for a given classification algorithm, namely C4.5, a well-known decision-tree algorithm. The two objectives to be minimized are the error rate and the size of the tree produced by C4....

The paper describes a counter example to the hypothesis which states that a greedy decision tree generation algorithm that constructs binary decision trees and branches on a single attribute-value pair rather than on all values of the selected attribute will always lead to a tree with fewer leaves for any given training set. We show also that RELIEFF is less myopic than other impurity functions...

In this paper, we discuss the power conservative indexing techniques for managing multi-attribute data broadcast on wireless channels. These indexing techniques, namely, index tree, signature and hybrid, aim at improving the battery power consumption of mobile clients. By taking into account the broadcast management factors such as clustering and scheduling, these three indexing schemes may sig...

Tree patterns (TP) is a simple and widely used fragment of XPath. The problem of containment in TP has been extensively studied previously. It was shown that the containment problem ranges from PTime to PSpace depending on the available constructs. In this paper we study the complexity of the containment problem for tree patterns with attribute value comparisons. We show that the complexity ran...

For defining attribute types to be used in the case representation, taxonomies occur quite often. The symbolic values at any node of the taxonomy tree are used as attribute values in a case or a query. A taxonomy type represents a relationship between the symbols through their position within the taxonomy-tree which expresses knowledge about the similarity between the symbols. This paper analyz...

Format specifications of data input are critical to model-based fuzz testing. Present methods cannot describe the format accurately, which leads to high redundancy in testing practices. In order to improve testing efficiency, we propose a grammar-driven approach to fuzz testing. Firstly, we build a formal model of data format using higher-order attribute grammars, and construct syntax tree on t...

Structured documents, such as program source texts, technical documentation, or XML data, comprise an important class of data in many applications. Structured documents are distinguished from flat text by their tree structure. In a program source text, this structure is the abstract syntax tree of the program. In a technical document, this structure is the division in chapters, sections, paragr...