Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction

For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the training examples and/or the computational costs associated with learning from them. In such circumstances, one question of practical importance is: if only n training examples can be selected, in what proportion should the classes be represented? In this article we help to answer this question by analyzing, for a fixed training-set size, the relationship between the class distribution of the training data and the performance of classification trees induced from these data. We study twenty-six data sets and, for each, determine the best class distribution for learning. The naturally occurring class distribution is shown to generally perform well when classifier performance is evaluated using undifferentiated error rate (0/1 loss). However, when the area under the ROC curve is used to evaluate classifier performance, a balanced distribution is shown to perform well. Since neither of these choices for class distribution always generates the best-performing classifier, we introduce a budget-sensitive progressive sampling algorithm for selecting training examples based on the class associated with each example. An empirical analysis of this algorithm shows that the class distribution of the resulting training set yields classifiers with good (nearly-optimal) classification performance

Asteroseismology and calibration of alpha Cen binary system

Using the oscillation frequencies of alpha Cen A recently discovered by Bouchy & Carrier, the available astrometric, photometric and spectroscopic data, we tried to improve the calibration of the visual binary system alpha Cen. With the revisited masses of Pourbaix et al. (2002) we do not succeed to obtain a solution satisfying all the seismic observational constraints. Relaxing the constraints on the masses, we have found an age t_alpha Cen=4850+-500 Myr, an initial helium mass fraction Y_i = 0.300+-0.008, and an initial metallicity (Z/X)_i=0.0459+-0.0019, with M_A=1.100+-0.006M_o and M_B=0.907+-0.006M_o for alpha Cen A&B.Comment: accepted for publication as a letter in A&

On Objective Measures of Rule Surprisingness

Most of the literature argues that surprisingness is an inherently subjective aspect of the discovered knowledge, which cannot be measured in objective terms. This paper departs from this view, and it has a twofold goal: (1) showing that it is indeed possible to define objective (rather than subjective) measures of discovered rule surprisingness; (2) proposing new ideas and methods for defining objective rule surprisingness measures

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

Neonatal Lupus Erythematosus: New Serologic Findings

A child with neonatal lupus was evaluated and found to possess serum anti Ro(SSA) antibodies. The cutaneous lesions and anti Ro(SSA) antibodies disappeared during the next 5 mo.The infant's mother was asymptomatic but possessed anti Ro(SSA) and anti La(SSB) antibodies

VINCI / VLTI observations of Main Sequence stars

Main Sequence (MS) stars are by far the most numerous class in the Universe. They are often somewhat neglected as they are relatively quiet objects (but exceptions exist), though they bear testimony of the past and future of our Sun. An important characteristic of the MS stars, particularly the solar-type ones, is that they host the large majority of the known extrasolar planets. Moreover, at the bottom of the MS, the red M dwarfs pave the way to understanding the physics of brown dwarfs and giant planets. We have measured very precise angular diameters from recent VINCI/VLTI interferometric observations of a number of MS stars in the K band, with spectral types between A1V and M5.5V. They already cover a wide range of effective temperatures and radii. Combined with precise Hipparcos parallaxes, photometry, spectroscopy as well as the asteroseismic information available for some of these stars, the angular diameters put strong constraints on the detailed models of these stars, and therefore on the physical processes at play.Comment: 5 pages, 3 figures. To appear in the Proceedings of IAU Symposium 219, "Stars as Suns", Editors A. Benz & A. Dupree, Astronomical Society of the Pacifi