Integrating Learning from Examples into the Search for Diagnostic Policies

This paper studies the problem of learning diagnostic policies from training examples. A diagnostic policy is a complete description of the decision-making actions of a diagnostician (i.e., tests followed by a diagnostic decision) for all possible combinations of test results. An optimal diagnostic policy is one that minimizes the expected total cost, which is the sum of measurement costs and misdiagnosis costs. In most diagnostic settings, there is a tradeoff between these two kinds of costs. This paper formalizes diagnostic decision making as a Markov Decision Process (MDP). The paper introduces a new family of systematic search algorithms based on the AO* algorithm to solve this MDP. To make AO* efficient, the paper describes an admissible heuristic that enables AO* to prune large parts of the search space. The paper also introduces several greedy algorithms including some improvements over previously-published methods. The paper then addresses the question of learning diagnostic policies from examples. When the probabilities of diseases and test results are computed from training data, there is a great danger of overfitting. To reduce overfitting, regularizers are integrated into the search algorithms. Finally, the paper compares the proposed methods on five benchmark diagnostic data sets. The studies show that in most cases the systematic search methods produce better diagnostic policies than the greedy methods. In addition, the studies show that for training sets of realistic size, the systematic search algorithms are practical on todays desktop computers

PuLSE-I: Deriving instances from a product line infrastructure

Reusing assets during application engineering promises to improve the efficiency of systems development. However, in order to benefit from reusable assets, application engineering processes must incorporate when and how to use the reusable assets during single system development. However, when and how to use a reusable asset depends on what types of reusable assets have been created.Product line engineering approaches produce a reusable infrastructure for a set of products. In this paper, we present the application engineering process associated with the PuLSE product line software engineering method - PuLSE-I. PuLSE-I details how single systems can be built efficiently from the reusable product line infrastructure built during the other PuLSE activities

Living Lives of Faith (Holiness)

In lieu of an abstract, below is the essay\u27s first paragraph. Each year on November 1st, The Roman Catholic Church celebrates the Feast of All Saints and encourages us to reflect on men and women of all ages who are models of holiness and heroes in the faith

Review of Student Performance in Developmental mathematics Courses Taught at Virginia Western Community College

The problem of this study was to determine changes that should be made by Virginia Western mathematics faculty to improve developmental mathematics instruction

Derived automorphism groups of K3 surfaces of Picard rank 1

We give a complete description of the group of exact autoequivalences of the bounded derived category of coherent sheaves on a K3 surface of Picard rank 1. We do this by proving that a distinguished connected component of the space of stability conditions is preserved by all autoequivalences, and is contractible

Engineering of spin-lattice relaxation dynamics by digital growth of diluted magnetic semiconductor CdMnTe

The technological concept of "digital alloying" offered by molecular-beam epitaxy is demonstrated to be a very effective tool for tailoring static and dynamic magnetic properties of diluted magnetic semiconductors. Compared to common "disordered alloys" with the same Mn concentration, the spin-lattice relaxation dynamics of magnetic Mn ions has been accelerated by an order of magnitude in (Cd,Mn)Te digital alloys, without any noticeable change in the giant Zeeman spin splitting of excitonic states, i.e. without effect on the static magnetization. The strong sensitivity of the magnetization dynamics to clustering of the Mn ions opens a new degree of freedom for spin engineering.Comment: 9 pages, 3 figure