Tag decision-trees [11 articles]

Abstract

This paper describes RESOLVE, a system that uses decision trees to learn how to classify coreferent phrases in the domain of business joint ventures. An experiment is presented in which the performance of RESOLVE is compared to the performance of a manually engineered set of rules for the same task. The results show that decision trees achieve higher performance than the rules in two of three evaluation metrics developed for the coreference task. In addition to achieving better performance than the rules, RESOLVE provides a framework that facilitates ...

Abstract

Significant time and effort has been devoted to finding feature representations of images in databases in order to enable content-based image retrieval (CBIR). Relevance feedback is a mechanism for improving retrieval precision over time by allowing the user to implicitly communicate to the system which of these features are relevant and which is not. We propose a relevance feedback retrieval system that, for each retrieval iteration, learns a decision tree to uncover a common thread between all images marked as relevant. ...

Abstract

We present an algorithm for compressing table constraints representing allowed or disallowed tuples. This type of constraint is used for example in configuration problems, where the satisfying tuples are read from a database. The arity of these constraints may be large. A generic GAC algorithm for such a constraint requires time exponential in the arity of the constraint to maintain GAC, but Bessi�re and R�gin showed in [1] that for the case of allowed tuples, GAC can be enforced in time ...

Abstract

The technology for building knowledge-based systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of ...

Abstract

The triage note field of the Emergency Department (ED) patient record describes the reason for the patient's visit, including specific symptoms and incidents. Here we present the Triage Note Temporal Information Extraction System (TN-TIES), which systematically processes triage note text and outputs a human and machine readable interpretation of the timing of the events leading up to the ED visit. TN-TIES consists of chunking, classification, and interpretation processing stages. The results at each stage are promising. This system is a first ...

Abstract

Decision trees have been applied to problems such as assigning protein function and predicting splice sites. How do these classifiers work, what types of problems can they solve and what are their advantages over alternatives? Many scientific problems entail labeling data items with one of a given, finite set of classes based on features of the data items. For example, oncologists classify tumors as different known cancer types using biopsies, patient records and other assays. Decision trees, such as C4.5 (ref. 1), ...

Abstract

Selecting the close-to-optimal collective algorithm based on the parameters of the collective call at run time is an important step in achieving good performance of MPI applications. In this paper, we explore the applicability of C4.5 decision trees to the MPI collective algorithm selection problem. We construct C4.5 decision trees from the measured algorithm performance data and analyze the decision tree properties and expected run time performance penalty. In cases we considered, results show that the C4.5 decision trees can be ...

Abstract

Abstract  Hierarchical multi-label classification (HMC) is a variant of classification where instances may belong to multiple classes at the same time and these classes are organized in a hierarchy. This article presents several approaches to the induction of decision trees for HMC, as well as an empirical study of their use in functional genomics. We compare learning a single HMC tree (which makes predictions for all classes together) to two approaches that learn a set of regular classification trees (one for each ...

Abstract

In this paper, we present a Case Based Reasoning (CBR) system for the retrieval of medical cases made up of a series of images with contextual information (such as the patient age, sex and medical history). Indeed, medical experts generally need varied sources of information (which might be incomplete) to diagnose a pathology. Consequently, we derive a retrieval framework from decision trees, which are well suited to process heterogeneous and incomplete information. To be integrated in the system, images are indexed ...

Abstract

In many learning problems, labelled examples are rare or expensive while numerous unlabelled and positive examples are available. However, most learning algorithms only use labelled examples. ...