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  • 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:
    AN ABSTRACT OF THE THESIS OF Hussein Saleh Almuallim for the degree of Doctor of Philosophy in

  • Relationship of pauses to problem solving events in mechanical design protocols

    Creator:
    Chamberlin, Martha J.
    Abstract:
    This thesis compares two methods for studying the problem-solving processes of mechanical design engineers. The first method, verbal protocol analysis, was applied by L. Stauffer to construct a problem-solving model of mechanical design. The second method, timing analysis, measures the time intervals separating drawing or speaking actions during the design...
    Resource Type:
    Masters Thesis
    Full Text:
    developed, it was applied to the 3 1/2 hours of protocol selected for the fine breakdown analysis. This was

  • 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:
    learning algorithm called UTILITYID3 is applied to a collection of training examples to discover

  • Three methods for estimating subpixel cover fractions in coarse resolution imagery

    Creator:
    Damon, Diane L.
    Abstract:
    Coarse resolution imagery, such as that produced by the MODIS instrument, poses the challenge of estimating sub-pixel proportions of di erent land cover types. This problem is di cult because of the variety and variability of vegetation within individual pixels. This thesis describes and compares two existing algorithms for estimating...
    Resource Type:
    Masters Thesis
    Full Text:
    ) of end member spectra. It can then be applied to predict abundances for new pixels. Let r∗ = (r∗1

  • Creating, Understanding and Applying Machine Learning Models of Multiple Species

    Creator:
    Griffioen, Arwen Twinkle E.
    Abstract:
    Many problems in ecology and conservation biology can be formulated and solved using machine learning algorithms for multi-label classification. This dissertation addresses three topics related to predicting the distributions of multiple species. It improves existing methods and proposes a new modeling paradigm to address the multi-species, multi-label problem. The first...
    Resource Type:
    Dissertation
    Full Text:
    are almost always the result of statistical or mathematical models applied to surveyed presences and

  • Shrunken learning rates do not improve AdaBoost on benchmark datasets

    Creator:
    Forrest, Daniel L. K.
    Abstract:
    Recent work has shown that AdaBoost can be viewed as an algorithm that maximizes the margin on the training data via functional gradient descent. Under this interpretation, the weight computed by AdaBoost, for each hypothesis generated, can be viewed as a step size parameter in a gradient descent search. Friedman...
    Resource Type:
    Masters Thesis
    Full Text:
    rates can improve the generalization accuracy of AdaBoost applied to clas- sification problems. Our

  • 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:
    of linear equations. Least squares methods are applied to solve these equations. Accuracy of the

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation
    Full Text:
    ] studies the general problem of MDP planning, which can be applied to the protection of endangered species

  • 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 is applied to solve the given problem instance. This search tree generated can be thought of as a

  • 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:
    interval on the difference in expected costs of two classifiers. These methods are applied to a large set