Signal Detection by Human Observers

Contains a report on a research project.This work was supported in part by United States Air Force (Contract AF19(604)-1728

Signal Detection by Human Observers

Contains research objectives and reports on one research project

Signal Detection by Human Observers

Contains research objectives and reports on one research project.U.S. Air Force Contract AF19(604)-1728, monitored by the Operational Applications Laboratory, Air Force Cambridge Research Cente

Extremal Dependence Indices: improved verification measures for deterministic forecasts of rare binary events

Copyright © 2011 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act September 2010 Page 2 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected] forecasts of rare events is challenging, in part because traditional performance measures degenerate to trivial values as events become rarer. The extreme dependency score was proposed recently as a nondegenerating measure for the quality of deterministic forecasts of rare binary events. This measure has some undesirable properties, including being both easy to hedge and dependent on the base rate. A symmetric extreme dependency score was also proposed recently, but this too is dependent on the base rate. These two scores and their properties are reviewed and the meanings of several properties, such as base-rate dependence and complement symmetry that have caused confusion are clarified. Two modified versions of the extreme dependency score, the extremal dependence index, and the symmetric extremal dependence index, are then proposed and are shown to overcome all of its shortcomings. The new measures are nondegenerating, base-rate independent, asymptotically equitable, harder to hedge, and have regular isopleths that correspond to symmetric and asymmetric relative operating characteristic curves

Balanced boosting with parallel perceptrons

The final publication is available at Springer via http://dx.doi.org/10.1007/11494669_26Proceedings of 8th International Work-Conference on Artificial Neural Networks, IWANN 2005, Vilanova i la Geltrú, Barcelona, Spain, June 8-10, 2005.Boosting constructs a weighted classifier out of possibly weak learners by successively concentrating on those patterns harder to classify. While giving excellent results in many problems, its performance can deteriorate in the presence of patterns with incorrect labels. In this work we shall use parallel perceptrons (PP), a novel approach to the classical committee machines, to detect whether a pattern’s label may not be correct and also whether it is redundant in the sense of being well represented in the training sample by many other similar patterns. Among other things, PP allow to naturally define margins for hidden unit activations, that we shall use to define the above pattern types. This pattern type classification allows a more nuanced approach to boosting. In particular, the procedure we shall propose, balanced boosting, uses it to modify boosting distribution updates. As we shall illustrate numerically, balanced boosting gives very good results on relatively hard classification problems, particularly in some that present a marked imbalance between class sizes.With partial support of Spain’s CICyT, TIC 01–572

A New Framework for the Assessment and Calibration of Medium Range Ensemble Temperature Forecasts

We present a new framework for the assessment and calibration of medium range ensemble temperature forecasts. The method is based on maximising the likelihood of a simple parametric model for the temperature distribution, and leads to some new insights into the predictability of uncertainty.Comment: Submitted to AS

Signal Detection by Human Observers

Contains reports on three research projects.United States Air Force (Contract AF19(604)-1728

Parallel Perceptrons, Activation Margins and Imbalanced Training Set Pruning

The final publication is available at Springer via http://dx.doi.org/10.1007/11492542_6Proceedings of Second Iberian Conference, IbPRIA 2005, Estoril, Portugal, June 7-9, 2005, Part IIA natural way to deal with training samples in imbalanced class problems is to prune them removing redundant patterns, easy to classify and probably over represented, and label noisy patterns that belonging to one class are labelled as members of another. This allows classifier construction to focus on borderline patterns, likely to be the most informative ones. To appropriately define the above subsets, in this work we will use as base classifiers the so–called parallel perceptrons, a novel approach to committee machine training that allows, among other things, to naturally define margins for hidden unit activations. We shall use these margins to define the above pattern types and to iteratively perform subsample selections in an initial training set that enhance classification accuracy and allow for a balanced classifier performance even when class sizes are greatly different.With partial support of Spain’s CICyT, TIC 01–572, TIN2004–0767

Using longitudinal survival probabilities to test field vigour estimates in sugar maple (Acer saccharum Marsh.)

Tree mortality is a major force driving forest dynamics. To foresters, however, tree mortality is often considered a loss in productivity. To reduce tree mortality, silvicultural systems, such as selection cuts, aim at removing trees that are more likely to die. In order to identify trees with higher risks of mortality, field classifications are employed that assess vigour based on external characteristics of trees. We used a novel longitudinal approach for estimating survival probabilities based on ring-width measurements, initially developed by Bigler and Bugmann [Bigler, C., Bugmann, H., 2004. Predicting the time of tree death using dendrochronological data. Ecol. Appl. 14 (3), 902-914], to parameterize a survival probability model for sugar maple (Acer saccharum Marsh.) and to test whether field-assessed tree vigour classes are corroborated by survival probabilities determined from radial growth history. Data from 56 dead and 321 live sugar maples were collected in stands in western Quebec (Canada) that had undergone a selection cut ≈10 years prior to sampling. Our results showed that tree vigour established from external defects and pathological symptoms, using the classification of Boulet [Boulet, B., 2005. D