We introduce another item in the already large list of techniques for attribute evaluation. Our algorithm consists in computing an attributes by reduction to normal form using a transducer operating on tree encodings of a cyclic representation of zippers. A zipper is a data structure introduced by Gérard Huet for representing a subtree together with its context, i.e. it is a tree with a focus t...

The naive Bayesian classiier provides a simple and eeective approach to classiier learning, but its attribute independence assumption is often violated in the real world. A number of approaches have sought to alleviate this problem. A Bayesian tree learning algorithm builds a decision tree, and generates a local naive Bayesian classiier at each leaf. The tests leading to a leaf can alleviate at...

It is the goal of classification and regression to build a data mining model that can be used for prediction. To construct such a model, we are given a set of training records, each having several attributes. These attributes can either be numerical (for example, age or salary) or categorical (for example, profession or gender). There is one distinguished attribute, the dependent attribute; the...

Attribute selection is generally considered as a challenging work in the development of image data mining oriented applications. Attribute subset selection is mainly an optimization problem, which involves searching the space of possible feature subsets to select the one that is optimal or nearly optimal with respect to the performance measures accuracy, complexity etc., of the application. Thi...

In this paper, we study power conservation techniques for multi-attribute queries on wireless data broadcast channels. Indexing data on broadcast channels can improve client filtering capability, while clustering and scheduling can reduce both access time and tune-in time. Thus, indexing techniques should be coupled with clustering and scheduling methods to reduce the battery power consumption ...

Attribute based encryption (ABE) and attribute based signature (ABS) provide flexible access control with authentication for data sharing between users, but realizing both functions will bring about too much computation burden. In this paper, we combine the advantages of CP-ABE with ABS and propose a ciphertext policy attribute based signcryption scheme. In our scheme, only legal receivers can ...

Attribute selection is generally considered as a challenging work in the development of image data mining oriented applications. Attribute subset selection is mainly an optimization problem, which involves searching the space of possible feature subsets to select the one that is optimal or nearly optimal with respect to the performance measures accuracy, complexity etc., of the application. Thi...

The Tree Augmented Naïve Bayes (TAN) classifier relaxes the sweeping independence assumptions of the Naïve Bayes approach by taking account of conditional probabilities. It does this in a limited sense, by incorporating the conditional probability of each attribute given the class and (at most) one other attribute. The method of boosting has previously proven very effective in improving the per...

In remote sensing, many target objects have highly irregular appearance. Especially natural objects — such as clouds, isotherms and curves of terrain elevation — are typically irregular in both shape and structure. This paper explains how irregular natural objects can be modelled and processed efficiently as attribute trees. First, we present a technique for extracting image topology and shape ...

Problem 2. Consider a classification problem where there is only one describing attribute A and one class attribute B. Both A and B have binary domains. Specifically, A has two values a0 and a1 while B has two values yes and no. We want to build a decision tree such that given a person, by looking at her/his A value, we predict her/his class label. Suppose that we already know the following sta...