Items where Author is "Ratsaby, Joel"
Number of items: 19.
Large-width machine learning algorithm. (2020)
Anthony, Martin; Ratsaby, Joel
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Classification based on prototypes with spheres of influence.
Anthony, Martin; Ratsaby, Joel
Large margin case-based reasoning.
Anthony, Martin; Ratsaby, Joel
Large width nearest prototype classification on general distance spaces.
Anthony, Martin; Ratsaby, Joel
Large-width bounds for learning half-spaces on distance spaces.
Anthony, Martin; Ratsaby, Joel
Learning bounds via sample width for classifiers on finite metric spaces.
Anthony, Martin; Ratsaby, Joel
Learning on finite metric spaces.
Anthony, Martin; Ratsaby, Joel
Maximal width learning of binary functions.
Anthony, Martin; Ratsaby, Joel
Maximal width learning of binary functions.
Anthony, Martin; Ratsaby, Joel
Maximal-margin case-based inference.
Anthony, Martin; Ratsaby, Joel
Multi-category classifiers and sample width.
Anthony, Martin; Ratsaby, Joel
Quantifying accuracy of learning via sample width.
Anthony, Martin; Ratsaby, Joel
Robust cutpoints in the logical analysis of numerical data.
Anthony, Martin; Ratsaby, Joel
Sample width for multi-category classifiers.
Anthony, Martin; Ratsaby, Joel
Using boxes and proximity to classify data into several categories.
Anthony, Martin; Ratsaby, Joel
A hybrid classifier based on boxes and nearest neighbors.
Anthony, Martin; Ratsaby, Joel
The performance of a new hybrid classifier based on boxes and nearest neighbors.
Anthony, Martin; Ratsaby, Joel
The performance of a new hybrid classifier based on boxes and nearest neighbors.
Anthony, Martin; Ratsaby, Joel
A probabilistic approach to case-based inference.
Anthony, Martin; Ratsaby, Joel