By Aysha Akther, Heung-Nam Kim, Majdi Rawashdeh, Abdulmotaleb El Saddik (auth.), Leila Kosseim, Diana Inkpen (eds.)
This e-book constitutes the refereed lawsuits of the twenty fifth Canadian convention on man made Intelligence, Canadian AI 2012, held in Toronto, Canada, in might 2012. The 23 standard papers, sixteen brief papers, and four papers from the Graduate pupil Symposium offered have been conscientiously reviewed and chosen for inclusion during this e-book. The papers disguise a extensive diversity of subject matters proposing unique paintings in all parts of man-made intelligence, both theoretical or applied.
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Additional resources for Advances in Artificial Intelligence: 25th Canadian Conference on Artificial Intelligence, Canadian AI 2012, Toronto, ON, Canada, May 28-30, 2012. Proceedings
LNCS, vol. 482, pp. 151–163. Springer, Heidelberg (1991) 7. : Statistical comparisons of classiﬁers over multiple data sets. Journal of Machine Learning Research 7, 1–30 (2006) 8. : Solving multiclass learning problems via error-correcting output codes. Journal of Artiﬁcial Intelligence Research 2, 263–286 (1995) 9. : Re-coding ecocs without re-training. Pattern Recognition Letters 31, 555–562 (2010) 10. : Binary tree of svm: A new fast multiclass training and cassiﬁcation algorithm. IEEE Transactions on Neural Networks 17(696-704) (2006) 11.
E. ωm = arg max P (ωi |x) ωi (2) In the case of LCO-ver1, the two most probable classes are found by choosing the two largest P (ωi ) , which are equivalent to the two most frequent classes among the neighbor instances. c} are chosen as probable classes. 1 Experimental Comparison Experimental Settings In order to present the results, ﬁrst, we discuss the experimental settings of the experiments. In order to investigate the relative performance of our proposed method, an empirical study was conducted.
Sources of Macros. We use three sources of macros: Wizard’s chunking phase [10,11], Macro-FF version CA-ED , and the manually constructed macros in Table 2. For Wizard, the default utility threshold was lowered to 150, 100, 100, 100, and 15 for logistics, blocksworld, mystery, pipesworld, and freecell, respectively, to produce macros in all domains. We capture the macros that result from Table 1. The parameters used to generate the instances and the training and test set size ranges. A description of the parameters can be found with each domain generator.