Ensembles of probability estimation trees for customer churn prediction

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

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)

Speech Driven Facial Animation

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