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Shuttle Landing Control Data Set

Below are papers that cite this data set, with context shown. Papers were automatically harvested and associated with this data set, in collaboration with Rexa.info.

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Christophe Giraud and Tony Martinez. ADYNAMIC INCREMENTAL NETWORK THAT LEARNS BY DISCRIMINATION. AA.

shuttle exp consists of the complete set of 278 instances resulting from expanding the 15 rules of the shuttle landing control (shuttle-l-c) dataset. 6 Reported results for hepatitis and shuttle-exp were gathered using 10-way cross validation. Results for the Monk problems used the provided training and test sets, and results for shuttle-l-c


Adil M. Bagirov and Julien Ugon. An algorithm for computation of piecewise linear function separating two sets. CIAO, School of Information Technology and Mathematical Sciences, The University of Ballarat.

accuracy (a mc in Tables 2 and 3) as described above. First accuracy is an indication of separation quality and the second one is an indication of multi-class classification quality. 5.2 Datasets The datasets used are the Shuttle control , the Letter recognition, the Landsat satellite image, the Pen-based recognition of handwritten and the Page blocks classification databases. Table 1


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