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Filtering by: Creator Mitchell, Hugh C. Remove constraint Creator: Mitchell, Hugh C. Advisor Dietterich, Thomas G. Remove constraint Advisor: Dietterich, Thomas G.

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  • Learning functional descriptions from examples

    Creator:
    Flann, Nicholas S.
    Abstract:
    The task of inductive learning from examples places constraints on the representation of training instances and concepts. These constraints are different from, and often incompatible with, the constraints placed on the representation by the performance task. This incompatibility is severe when learning functional concepts and explains why previous researchers have...
    Resource Type:
    Masters Thesis
    Full Text:
    learn the concept, (b) the biases of the learning pro- gram are very simple, and (c) the learning

  • Simulator-Defined MDP Planning with Applications in Natural Resource Management

    Creator:
    Alkaee Taleghan, Majid
    Abstract:
    This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
    Resource Type:
    Dissertation
    Full Text:
    drawn to shrink the confidence interval as quickly as possible? (c) how can we find the optimal policy

  • A study of distance-based machine learning algorithms

    Creator:
    Wettschereck, Dietrich
    Abstract:
    Distance-based algorithms are machine learning algorithms that classify queries by computing distances between these queries and a number of internally stored exemplars. Exemplars that are closest to the query have the largest in uence on the classi cation assigned to the query. Two speci c distance-based algorithms, the nearest neighbor...
    Resource Type:
    Dissertation
    Full Text:
    existing distance-based algorithms, (b) several new distance-based algorithms, and (c) an experimentally

  • An empirical study into learning through experimentation

    Creator:
    Ruff, Ritchey Alvin
    Abstract:
    A key aspect of how we understand the world revolves around an ability to manipulate our surroundings to experiment. From the scientific method through theories of child development, the ability to experiment is deemed critical; however, few studies have been performed to understand the strengths and weaknesses of different experimental...
    Resource Type:
    Dissertation
    Full Text:
    number of hypotheses were possible, (b) each experiment had a large number of outcomes, and (c

  • Protein secondary structure prediction using conditional random fields and profiles

    Creator:
    Shen, Rongkun
    Abstract:
    Protein secondary structure prediction plays a pivotal role in predicting protein folding in three-dimensions. Its task is to assign each residue one of the three secondary structure classes helix, strand, or random coil. This is an instance of the problem of sequential supervised learning in machine learning. This thesis describes...
    Resource Type:
    Masters Thesis
    Full Text:
    --- Note: a Nucleic acid sequences, as of Dec. 15, 2005. b Protein sequences, as of Jan. 10, 2006. c

  • Expert-gate algorithm

    Creator:
    Joshi, Varad Vidyadhar
    Abstract:
    The goal of Inductive Learning is to produce general rules from a set of seen examples, which can then be applied to other unseen examples. ID3 is an inductive learning algorithm that can be used for the classification task. The input to the algorithm is a set of tuples of...
    Resource Type:
    Masters Thesis
    Full Text:
    Description of DNF Target Concepts 48 B Description of CNF Target Concepts 49 C Description of Expert-Gate

  • Concept coverage and its application to two learning tasks

    Creator:
    Almuallim, Hussein Saleh
    Abstract:
    The coverage of a learning algorithm is the number of concepts that can be learned by that algorithm from samples of a given size for given accuracy and confidence parameters. This thesis begins by asking whether good learning algorithms can be designed by maximizing their coverage. There are three questions...
    Resource Type:
    Dissertation
    Full Text:
    a basis is known in the machine learning community as the bias of the learning algorithm [Mitchell

  • Understanding and improving error-correcting output coding

    Creator:
    Kong, Eun Bae
    Abstract:
    Error-correcting output coding (ECOC) is a method for converting a k-classsupervised learning problem into a large number L of two-class supervised learningproblems and then combining the results of these L evaluations. Previous researchhas shown that ECOC can dramatically improve the classi cation accuracy of supervisedlearning algorithms that learn to classify...
    Resource Type:
    Dissertation
    Full Text:
    posterior probabilities is demonstrated with overlapping classes and a simple reject option task. c

  • An implementation and initial test of generalized radial basis functions

    Creator:
    Wettschereck, Dietrich
    Abstract:
    Generalized Radial Basis Functions were used to construct networks that learn input-output mappings from given data. They are developed out of a theoretical framework for approximation based on regularization techniques and represent a class of three-layer networks similar to backpropagation networks with one hidden layer. A network using Gaussian base...
    Resource Type:
    Masters Thesis
    Full Text:
    . Three centers A,B,C and three data points 11, 12, and 13. 7 3. The GRBF network architecture. 8 4

  • An investigation of the search space of Lenat's AM program

    Creator:
    Mishra, Prafulla K.
    Abstract:
    AM is a computer program written by Doug Lenat that discovers elementary mathematics starting from some initial knowledge of set theory. The success of this program is not clearly understood. This work is an attempt to explore the search space of AM in order to understand the success and eventual...
    Resource Type:
    Masters Thesis
    Full Text:
    heuristics b) the representation of concepts and c) the initial knowledge base. The author of AM, Doug Lenat

  • Grasshopper Infestation Prediction : An Application of Data Mining to Ecological Modeling

    Creator:
    Bunjongsat, Waranun
    Abstract:
    This thesis presents a case study of applying machine learning tools to build a predictive model of annual infestations of grasshoppers in Eastern Oregon. The purpose of the study was two-fold. First, we wanted to develop a predictive model. Second, we wanted to explore the capabilities of existing machine learning...
    Resource Type:
    Capstone Project
    Full Text:
    _____________________________________________________ 48 B.6 Prediction and Evaluation________________________________________________ 51 Appendix C

  • Activity recognition in desktop environments

    Creator:
    Shen, Jianqiang
    Abstract:
    Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
    Resource Type:
    Dissertation
    Full Text:
    inference algorithm [Natarajan et al., 2008]. c©Copyright by Jianqiang Shen March 19, 2009 All Rights

  • Applying machine learning for prediction, recommendation, and integration

    Creator:
    Bao, Xinlong
    Abstract:
    This dissertation explores the idea of applying machine learning technologies to help computer users find information and better organize electronic resources, by presenting the research work conducted in the following three applications: FolderPredictor, Stacking Recommendation Engines, and Integrating Learning and Reasoning. FolderPredictor is an intelligent desktop software tool that helps...
    Resource Type:
    Dissertation
    Full Text:
    information propagated from other classifiers. c©Copyright by Xinlong Bao August 24, 2009 All Rights

  • Reinforcement learning for job-shop scheduling

    Creator:
    Zhang, Wei, 1960-
    Resource Type:
    Dissertation
    Full Text:
    applying reinforcement learning algorithms to discover good domain-speci�c heuristics automatically for

  • Correct abstraction in counter-planning : a knowledge compilation approach

    Creator:
    Flann, Nicholas S.
    Abstract:
    Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach...
    Resource Type:
    Dissertation
    Full Text:
    Specification C Example run for KRK Problem 190 196 203 List of Figures 1.1 Two similar chess positions

  • 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:
    unchanged. c is an arbitrary positive cost value

  • Machine learning in engineering : techniques to speed up numerical optimization

    Creator:
    Cerbone, G. (Giuseppe)
    Abstract:
    Many important application problems in engineering can be formalized as nonlinear optimization tasks. However, numerical methods for solving such problems are brittle and do not scale well. For example, these methods depend critically on choosing a good starting point from which to perform the optimization search. In high-dimensional spaces, numerical...
    Resource Type:
    Dissertation
    Full Text:
    Bibliography 129 Appendices 136 A Simplifying Assumptions 136 B Objective Function 138 C Mathematica in the

  • Calibrating recurrent sliding window classifiers for sequential supervised learning

    Creator:
    Joshi, Saket Subhash
    Abstract:
    Sequential supervised learning problems involve assigning a class label to each item in a sequence. Examples include part-of-speech tagging and text-to-speech mapping. A very general-purpose strategy for solving such problems is to construct a recurrent sliding window (RSW) classifier, which maps some window of the input sequence plus some number...
    Resource Type:
    Masters Thesis
    Full Text:
    (c) are all random. There is no point in learning. 001 (a) and (b) are random but there is a pattern

  • 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:
    diagnostic policies that seek to minimize the expected total cost of diagnosis. c Copyright by Valentina

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . 147 B Design evolution of explanations in Chapter 4 and 5 . . . . . . . . . . . . . 148 C More about