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Filtering by: Creator Palo, D. Remove constraint Creator: Palo, D. Subject Machine learning Remove constraint Subject: Machine learning

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  • Learning cost-sensitive diagnostic policies from data

    Creator:
    Zubek, Valentina Bayer
    Abstract:
    In its simplest form, the process of diagnosis is a decision-making process in which the diagnostician performs a sequence of tests culminating in a diagnostic decision. For example, a physician might perform a series of simple measurements (body tem- perature, weight, etc.) and laboratory measurements (white blood count, CT scan,...
    Resource Type:
    Dissertation
    Full Text:
    supervised learning. Formally, given a sample of labeled examples (x; y) drawn from a distribution D(x; y

  • Methods for cost-sensitive learning

    Creator:
    Margineantu, Dragos D.
    Abstract:
    Many approaches for achieving intelligent behavior of automated (computer) systems involve components that learn from past experience. This dissertation studies computational methods for learning from examples, for classification and for decision making, when the decisions have different non-zero costs associated with them. Many practical applications of learning algorithms, including transaction...
    Resource Type:
    Dissertation
    Full Text:
    be rigorous. He has been very influential in my thinking. I owe special debts to Bruce D' Ambrosio

  • Learning diagnostic policies from examples by systematic search

    Creator:
    Oregon State University. Dept. of Computer Science and Zubek, Valentina Bayer
    Abstract:
    A diagnostic policy species what test to perform next based on the results of previous tests and when to stop and make a diagnosis. Cost-sensitive diagnostic policies perform tradeoffs between (a) the costs of tests and (b) the costs of misdiagnoses. An optimal diagnostic policy minimizes the expected total cost....
    Resource Type:
    Research Paper
    Full Text:
    cumulative BDelta� Cost results of alg� over alg on a given domain D� across all � misdiagnosis cost levels

  • Representations and algorithms for efficient inference in Bayesian networks

    Creator:
    Takikawa, Masami
    Abstract:
    Bayesian networks are used for building intelligent agents that act under uncertainty. They are a compact representation of agents' probabilistic knowledge. A Bayesian network can be viewed as representing a factorization of a full joint probability distribution into the multiplication of a set of conditional probability distributions. Independence of causal...
    Resource Type:
    Dissertation
    Full Text:
    network in figure 1.1, the joint proba­ bility of nodes D and E, P(D, E), can be computed in several ways

  • Constructive induction for improved learning of boolean functions

    Creator:
    Drake, Peter (Peter Dudey), 1970-
    Abstract:
    Supervised learning programs, such as decision tree learners and neural networks, often must learn Boolean functions. The concept being learned may not easily be expressed in terms of the atomic features given. Constructive induction automatically produces higher level features (combinations of the atomic features), which can improve learning performance. The...
    Resource Type:
    Masters Thesis
    Full Text:
    spurious feature D which is true for half of the cases. One approach to dealing with feature interaction

  • Machine learning for cognitive networks : technology assessment and research challenges

    Creator:
    Oregon State University. Dept. of Computer Science, Dietterich, Thomas Glen, and Langley, Pat
    Abstract:
    The field of machine learning has made major strides over the last 20 years. This document summarizes the major problem formulations that the discipline has studied, then reviews three tasks in cognitive networking and briefly discusses how aspects of those tasks fit these formulations. After this, it discusses challenges for...
    Resource Type:
    Research Paper
    Full Text:
    Expertise 2164 Staunton Court Palo Alto, CA 94306 Draft of May 11, 2003. Abstract The field of machine

  • Theoretical and implementation improvements for difference evaluation functions

    Creator:
    Colby, Mitchell Kataichi
    Abstract:
    Multiagent learning with cooperative coevolutionary algorithms is a critical area of research, and is relevant to many real-world applications including air traffic control, distributed sensor network control, and game-theoretic applications such as border patrol. A key difficulty in multiagent learning is the credit assignment problem, where the impact of each...
    Resource Type:
    Dissertation

  • Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale

    Creator:
    Hooper, Samuel
    Abstract:
    Developing accurate predictive distribution models requires adequately representing relevant spatial and temporal scales, as these scales are ultimately reflective of the relationships between distributions and influential environmental conditions. In this research, we considered both spatial and temporal scale and the influence each has on predicting broad-scale distributions of two disparate...
    Resource Type:
    Masters Thesis
    Full Text:
    /S0099-1112(15)30100-2. Ives, Anthony R., and Eric D. Klopfer. 1997. “Spatial Variation in Abundance

  • Lamb Wave Mode Decomposition and Its Applications in Structural Health Monitoring

    Creator:
    Zoubi, Ahmad Bassil
    Abstract:
    Structural health monitoring (SHM) systems perform automated non-destructive damage detection and characterization for a variety of large structures including civil structures such as bridges and aerospace structures such as aircrafts and space vehicles. The goals of SHM include preventing catastrophic structural failures, increasing reliability, reducing maintenance costs, and increasing the...
    Resource Type:
    Dissertation
    Full Text:
    after reassignment; (d) The estimated ridge curves for the S0 and A0 modes. The black dashed lines