4 Result(s)
within
Chapter
Ian Davidson
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Chapter and Conference Paper
Constrained Tensor Decomposition via Guidance: Increased Inter and Intra-Group Reliability in fMRI Analyses
Recently, Davidson and his colleagues introduced a promising new approach to analyzing functional Magnetic Resonance Imaging (fMRI) that suggested a more appropriate analytic approach is one that views the spa...
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Chapter and Conference Paper
When Efficient Model Averaging Out-Performs Boosting and Bagging
The Bayes optimal classifier (BOC) is an ensemble technique used extensively in the statistics literature. However, compared to other ensemble techniques such as bagging and boosting, BOC is less known and rar...
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Chapter and Conference Paper
Measuring Constraint-Set Utility for Partitional Clustering Algorithms
Clustering with constraints is an active area of machine learning and data mining research. Previous empirical work has convincingly shown that adding constraints to clustering improves performance, with respe...
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Chapter and Conference Paper
Agglomerative Hierarchical Clustering with Constraints: Theoretical and Empirical Results
We explore the use of instance and cluster-level constraints with agglomerative hierarchical clustering. Though previous work has illustrated the benefits of using constraints for non-hierarchical clustering, ...
