Comment: Boosting Algorithms: Regularization, Prediction and Model Fitting

The authors are doing the readers of Statistical Science a true service with a well-written and up-to-date overview of boosting that originated with the seminal algorithms of Freund and Schapire. Equally, we are grateful for high-level software that will permit a larger readership to experiment with, or simply apply, boosting-inspired model fitting. The authors show us a world of methodology that illustrates how a fundamental innovation can penetrate every nook and cranny of statistical thinking and practice. They introduce the reader to one particular interpretation of boosting and then give a display of its potential with extensions from classification (where it all started) to least squares, exponential family models, survival analysis, to base-learners other than trees such as smoothing splines, to degrees of freedom and regularization, and to fascinating recent work in model selection. The uninitiated reader will find that the authors did a nice job of presenting a certain coherent and useful interpretation of boosting. The other reader, though, who has watched the business of boosting for a while, may have quibbles with the authors over details of the historic record and, more importantly, over their optimism about the current state of theoretical knowledge. In fact, as much as ``the statistical view'' has proven fruitful, it has also resulted in some ideas about why boosting works that may be misconceived, and in some recommendations that may be misguided. [arXiv:0804.2752]Comment: Published in at http://dx.doi.org/10.1214/07-STS242B the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Prospects for Redshifted 21-cm observations of quasar HII regions

The introduction of low-frequency radio arrays over the coming decade is expected to revolutionize the study of the reionization epoch. Observation of the contrast in redshifted 21cm emission between a large HII region and the surrounding neutral IGM will be the simplest and most easily interpreted signature. We find that an instrument like the planned Mileura Widefield Array Low-Frequency Demonstrator (LFD) will be able to obtain good signal to noise on HII regions around the most luminous quasars, and determine some gross geometric properties, e.g. whether the HII region is spherical or conical. A hypothetical follow-up instrument with 10 times the collecting area of the LFD (MWA-5000) will be capable of mapping the detailed geometry of HII regions, while SKA will be capable of detecting very narrow spectral features as well as the sharpness of the HII region boundary. The MWA-5000 will discover serendipitous HII regions in widefield observations. We estimate the number of HII regions which are expected to be generated by quasars. Assuming a late reionization at z~6 we find that there should be several tens of quasar HII regions larger than 4Mpc at z~6-8 per field of view. Identification of HII regions in forthcoming 21cm surveys can guide a search for bright galaxies in the middle of these regions. Most of the discovered galaxies would be the massive hosts of dormant quasars that left behind fossil HII cavities that persisted long after the quasar emission ended, owing to the long recombination time of intergalactic hydrogen. A snap-shot survey of candidate HII regions selected in redshifted 21cm image cubes may prove to be the most efficient method for finding very high redshift quasars and galaxies.Comment: 14 pages, 8 figures. Submitted to Ap

New hydrogen-like potentials

Using the modified factorization method introduced by Mielnik, we construct a new class of radial potentials whose spectrum for l=0 coincides exactly with that of the hydrogen atom. A limiting case of our family coincides with the potentials previously derived by Abraham and MosesComment: 6 pages, latex, 2 Postscript figure

Boosted Classification Trees and Class Probability/Quantile Estimation

The standard by which binary classifiers are usually judged, misclassification error, assumes equal costs of misclassifying the two classes or, equivalently, classifying at the 1/2 quantile of the conditional class probability function P[y = 1|x]. Boosted classification trees are known to perform quite well for such problems. In this article we consider the use of standard, off-the-shelf boosting for two more general problems: 1) classification with unequal costs or, equivalently, classification at quantiles other than 1/2, and 2) estimation of the conditional class probability function P[y = 1|x]. We first examine whether the latter problem, estimation of P[y = 1|x], can be solved with Logit- Boost, and with AdaBoost when combined with a natural link function. The answer is negative: both approaches are often ineffective because they overfit P[y = 1|x] even though they perform well as classifiers. A major negative point of the present article is the disconnect between class probability estimation and classification. Next we consider the practice of over/under-sampling of the two classes. We present an algorithm that uses AdaBoost in conjunction with Over/Under-Sampling and Jittering of the data (“JOUS-Boost”). This algorithm is simple, yet successful, and it preserves the advantage of relative protection against overfitting, but for arbitrary misclassification costs and, equivalently, arbitrary quantile boundaries. We then use collections of classifiers obtained from a grid of quantiles to form estimators of class probabilities. The estimates of the class probabilities compare favorably to those obtained by a variety of methods across both simulated and real data sets

Modulation of Fibrosis in Systemic Sclerosis by Nitric Oxide and Antioxidants

Systemic sclerosis (scleroderma: SSc) is a multisystem, connective tissue disease of unknown aetiology characterized by vascular dysfunction, autoimmunity, and enhanced fibroblast activity resulting in fibrosis of the skin, heart, and lungs, and ultimately internal organ failure, and death. One of the most important and early modulators of disease activity is thought to be oxidative stress. Evidence suggests that the free radical nitric oxide (NO), a key mediator of oxidative stress, can profoundly influence the early microvasculopathy, and possibly the ensuing fibrogenic response. Animal models and human studies have also identified dietary antioxidants, such as epigallocatechin-3-gallate (EGCG), to function as a protective system against oxidative stress and fibrosis. Hence, targeting EGCG may prove a possible candidate for therapeutic treatment aimed at reducing both oxidant stress and the fibrotic effects associated with SSc