37 research outputs found

    Bagging ensemble selection for regression

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    Bagging ensemble selection (BES) is a relatively new ensemble learning strategy. The strategy can be seen as an ensemble of the ensemble selection from libraries of models (ES) strategy. Previous experimental results on binary classification problems have shown that using random trees as base classifiers, BES-OOB (the most successful variant of BES) is competitive with (and in many cases, superior to) other ensemble learning strategies, for instance, the original ES algorithm, stacking with linear regression, random forests or boosting. Motivated by the promising results in classification, this paper examines the predictive performance of the BES-OOB strategy for regression problems. Our results show that the BES-OOB strategy outperforms Stochastic Gradient Boosting and Bagging when using regression trees as the base learners. Our results also suggest that the advantage of using a diverse model library becomes clear when the model library size is relatively large. We also present encouraging results indicating that the non negative least squares algorithm is a viable approach for pruning an ensemble of ensembles

    Ensembles of probability estimation trees for customer churn prediction

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    Customer churn prediction is one of the most, important elements tents of a company's Customer Relationship Management, (CRM) strategy In tins study, two strategies are investigated to increase the lift. performance of ensemble classification models, i.e (1) using probability estimation trees (PETs) instead of standard decision trees as base classifiers; and (n) implementing alternative fusion rules based on lift weights lot the combination of ensemble member's outputs Experiments ale conducted lot font popular ensemble strategics on five real-life chin n data sets In general, the results demonstrate how lift performance can be substantially improved by using alternative base classifiers and fusion tides However: the effect vanes lot the (Idol cut ensemble strategies lit particular, the results indicate an increase of lift performance of (1) Bagging by implementing C4 4 base classifiets. (n) the Random Subspace Method (RSM) by using lift-weighted fusion rules, and (in) AdaBoost, by implementing both

    Some remarks on fluid flow in hourglasses

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    In the paper the authors analyse different shapes of an hourglass for the linearity of their graduation. We also assume that any hourglass (more precisely, each of the two congruent parts) has the shape of a solid of revolution and any cross section at height h of this hourglass depends on the base radius r, i.e. h = ƒ(r)

    A certain approach to Kripke semantics for normal modal logics

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    In this paper the authors propose a method of verifying formulae in normal modal logics. In order to show that a formula α is a thesis of a normal modal logic, a set of decomposition rules for any formula is given. These decomposition rules are based on the symbols of assertion and rejection of formulae

    Investigation of tribological properties of the intermetallics alloys

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    W pracy przedstawiono wyniki badań właściwości tribologicznych wybranych intermetali w warunkach tarcia suchego. Określono wartość zużycia masowego badanych materiałów i żeliwnej przeciwpróbki. Przeprowadzono analizę mikroskopową zmian stanu powierzchni w celu identyfikacji mechanizmów zniszczenia intermetali.The paper presents tribological tests results of the selected intermetallics alloys in the conditions of dry friction . Tribological properties of the intermetallics alloys was investigated by mass wear. The microscopic examinations of the samples of intermetallics alloys in order to identify mechanisms of destruction have been determined

    Agent-Based Gesture Tracking

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    Speech Driven Facial Animation

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    The results reported in this article are an integral part of a larger project aimed at achieving perceptually realistic animations, including the individualized nuances, of three-dimensional human faces driven by speech. The audiovisual system that has been developed for learning the spatio-temporal relationship between speech acoustics and facial animation is described, including video and speech processing, pattern analysis, and MPEG-4 compliant facial animation for a given speaker. In particular, we propose a perceptual transformation of the speech spectral envelope, which is shown to capture the dynamics of articulatory movements. An efficient nearest-neighbor algorithm is used to predict novel articulatory trajectories from the speech dynamics. The results are very promising and suggest a new way to approach the modeling of synthetic lip motion of a given speaker driven by his/her speech. This would also provide clues toward a more general cross-speaker realistic animation
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