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This paper outlines the concept of sequential design for classification, and the extension of an existing state-of-the-art research platform for surrogate modeling to handle classification problems with sequential design.
National sport federations handle classification on the lower levels.
For international skiing competitions, classification is conducted by International Paralympic Committee (IPC) Alpine Skiing and IPC Nordic Skiing, while national federations such as Alpine Canada handle classification for domestic competitions.
LDA can handle classification problems where the within-class frequencies are unequal and is well-regularized even when the data dimension is large such as in [ 19].
Weka (Waikato Environment for Knowledge Analysis) is a Java open source package that collects the most popular algorithms to handle classification, numeric prediction, or clustering problems.
In a subsequent work, Pontes et al. [ 23] extended the basic SPA to handle classification problems by merging with linear discriminate analysis (LDA), which results in the so-called SPA-LDA method.
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However, the relative importance of potential input variables and the long training process have often been criticized and hence limited its application in handling classification problems.
A national federation such as Alpine Canada handles classification for domestic competitions.
Before the IPC-NS took over classification, a number of organizations handled classification based on the type of disability.
A two-person panel that includes at least one person with a medical background handles classification at international competitions.
IBSA handles classification for a number of sports internationally including five-a-side football, goalball and judo.
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