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  • Exact learning of unordered tree patterns from queries

    Creator:
    Oregon State University. Dept. of Computer Science, Amoth, Thomas R., Cull, Paul, 1943-, and Tadepalli, Prasad
    Abstract:
    We consider learning tree patterns from queries extending our preceding work [Amoth, Cull, & Tadepalli, 1998]. The instances in this paper are unordered trees with nodes labeled by constant identifiers. The concepts are tree patterns and unions of tree patterns (unordered forests) with leaves labeled with constants or variables. A...
    Resource Type:
    Research Paper
    Full Text:
    95m.dvi Exact Learning of Unordered Tree Patterns From Queries Thomas R

  • Exact learning of tree patterns

    Creator:
    Amoth, Thomas R.
    Abstract:
    Tree patterns are natural candidates for representing rules and hypotheses in many tasks such as information extraction and symbolic mathematics. A tree pattern is a tree with labeled nodes where some of the leaves may be labeled with variables, whereas a tree instance has no variables. A tree pattern matches...
    Resource Type:
    Dissertation

  • Learning classification rules by randomized iterative local search

    Creator:
    Chisholm, Michael (Michael Andrew), 1974-
    Abstract:
    Learning easily understandable decision rules from examples is one of the classic problems in machine learning. Most learning algorithms for this problem employ some variation of a greedy separate-and-conquer algorithm. In this paper, we describe a system called LERILS that learns highly accurate and comprehensible rules from examples using a...
    Resource Type:
    Masters Thesis
    Full Text:
    the classic problems in machine learning. Most learning algorithms for this problem employ some

  • Structured gradient boosting

    Creator:
    Parker, Charles (Charles Lincoln)
    Abstract:
    The goal of many machine learning problems can be formalized as the creation of a function that can properly classify an input vector, given a set of examples of that function. While this formalism has produced a number of success stories, there are notable situations in which it fails. One...
    Resource Type:
    Dissertation
    Full Text:
    Boosting Abstract approved: Prasad Tadepalli The goal of many machine learning problems can be

  • 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:
    Inductive Learning is to produce general rules from a set of seen examples, which can then be applied to

  • A probabilistic framework and algorithms for modeling and analyzing multi-instance data

    Creator:
    Behmardi, Behrouz
    Abstract:
    Multi-instance data, in which each object (e.g., a document) is a collection of instances (e.g., word), are widespread in machine learning, signal processing, computer vision, bioinformatic, music, and social sciences. Existing probabilistic models, e.g., latent Dirichlet allocation (LDA), probabilistic latent semantic indexing (pLSI), and discrete component analysis (DCA), have been...
    Resource Type:
    Dissertation
    Full Text:
    collection of instances (e.g., word), are widespread in machine learning, signal processing, computer vision

  • Predicting activity type from accelerometer data

    Creator:
    Zheng, Yonglei
    Abstract:
    The study of physical activity is important in improving people’s health as it can help people understand the relationship between physical activity and health. Accelerometers, due to its small size, low cost, convenience and its ability to provide objective information about the frequency, intensity, and duration of physical activity, has...
    Resource Type:
    Masters Thesis
    Full Text:
    activity, has become the method of choice in measuring physical activity. Machine learning algorithms

  • Multi-instance multi-label learning : algorithms and applications to bird bioacoustics

    Creator:
    Briggs, Forrest
    Abstract:
    We consider the problem of supervised classification of bird species from audio recordings in a real-world acoustic monitoring scenario (i.e. audio data is collected in the field with an omnidirectional microphone, without human supervision). Obtaining better data about bird activity can assist conservation efforts, and improve our understanding of their...
    Resource Type:
    Dissertation
    Full Text:
    , traditional observation methods are labor- intensive. Most prior work on machine learning for bird song is