A logic boosting approach to inducing multiclass alternating decision trees

The alternating decision tree (ADTree) is a successful classification technique that combine decision trees with the predictive accuracy of boosting into a ser to interpretable classification rules. The original formulation of the tree induction algorithm restricted attention to binary classification problems. This paper empirically evaluates several methods for extending the algorithm to the multiclass case by splitting the problem into several two-class LogitBoost procedure to induce alternating decision trees directly. Experimental results confirm that this procedure is comparable with methods that are based on the original ADTree formulation in accuracy, while inducing much smaller trees

Benchmarking attribute selection techniques for discrete class data mining

Data engineering is generally considered to be a central issue in the development of data mining applications. The success of many learning schemes, in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes. The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. Attribute selection generally involves a combination of search and attribute utility estimation plus evaluation with respect to specific learning schemes. This leads to a large number of possible permutation and has led to a situation where very few benchmark studies have been conducted. This paper presents a benchmark comparison of several attribute selection methods for supervised classification. All the methods produce an attribute ranking, a useful devise for isolating the individual merit of an attribute. Attribute selection is achieved by cross-validating the attribute rankings with respect to a classification learner to find the best attributes. Results are reported for a selection of standard data sets and two diverse learning schemes C4.5 and naïve Bayes

Data mining in bioinformatics using Weka

The Weka machine learning workbench provides a general purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it

Draft genome sequence of the Streptococcus pneumoniae Avery strain A66

We have used HiSeq 2000 technology to generate a draft genome sequence of Streptococcus pneumoniae strain A66. This is a common study strain used in investigations of pneumococcal bacterium-host interactions and was used in the seminal genetic studies of Avery et al

How Do You Build a "Culture of Health"? A Critical Analysis of Challenges and Opportunities from Medical Anthropology.

The Robert Wood Johnson Foundation's Culture of Health Action Framework aims to "make health a shared value" and improve population health equity through widespread culture change. The authors draw upon their expertise as anthropologists to identify 3 challenges that they believe must be addressed in order to effectively achieve the health equity and population health improvement goals of the Culture of Health initiative: clarifying and demystifying the concept of "culture," contextualizing "community" within networks of power and inequality, and confronting the crises of trust and solidarity in the contemporary United States. The authors suggest that those who seek to build a "Culture of Health" refine their understanding of how "culture" is experienced, advocate for policies and practices that break down unhealthy consolidations of power, and innovate solutions to building consensus in a divided nation

Weka: A machine learning workbench for data mining

The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user interfaces are provided for data exploration, for setting up large-scale experiments on distributed computing platforms, and for designing configurations for streamed data processing. These interfaces constitute an advanced environment for experimental data mining. The system is written in Java and distributed under the terms of the GNU General Public License

Predicting C-H/π\pi interactions with nonlocal density functional theory

We examine the performance of a recently developed nonlocal density functional in predicting a model noncovalent interaction, the weak bond between an aromatic $\pi$ system and an aliphatic C-H group. The new functional is a significant improvement over traditional density functionals, providing results which compare favorably to high-level quantum-chemistry techniques but at considerably lower computational cost. Interaction energies in several model C-H/$\pi$ systems are in generally good agreement with coupled-cluster calculations, though equilibrium distances are consistently overpredicted when using the revPBE functional for exchange. The new functional correctly predicts changes in energy upon addition of halogen substituents.Comment: 5 pages, 4 figure

The emergence of mecC methicillin-resistant Staphylococcus aureus.

The report of methicillin-resistant Staphylococcus aureus (MRSA) encoding a divergent mecA gene in 2011 was highly significant. This homologue, designated mecC, poses diagnostic problems with the potential to be misdiagnosed as methicillin-sensitive S. aureus, with important potential consequences for individual patients and for the surveillance of MRSA. mecC MRSA have now been reported from 13 European countries and have been isolated from 14 different host species, with evidence of a recent increase in Denmark. The emergence of mecC MRSA is a topic of interest to human and veterinary microbiology, and we consider it timely to review here its discovery and subsequent investigation.Our work on S. aureus is supported by a Medical Research Council (MRC) Partnership Award to M.A.H and funding to G.K.P from PetPlan Charitable Trust, the British Society for Antimicrobial Chemotherapy, and the Cambridge–Africa Alborada Research Fund.This is the final published version distributed under a Creative Commons Attribution License 2.0, which can also be found on the publisher's website at: http://www.cell.com/trends/microbiology/abstract/S0966-842X(13)00226-

Great Lakes all-weather ice information system

A system is described which utilizes an X-band Side-Looking-Airborne-Radar (SLAR) for determining type, location, and aerial distribution of the ice cover in the Great Lakes and an airborne, S-band, short pulse radar for obtaining ice thickness. The SLAR system is currently mounted aboard a U.S. Coast Guard C-130B aircraft. Digitized SLAR data are relayed in real-time via the NOAA-GOES-1 satellite in geosynchronous orbit to the U.S. Coast Guard Ice Center in Cleveland, Ohio. SLAR images along with hand-drawn interpretative ice charts for various winter shipping areas in the Great Lakes are broadcast to facsimile recorders aboard Great Lakes vessels. The operational aspects of this ice information system are being demonstrated by NASA, U.S. Coast Guard, and NOAA/National Weather Service. Results from the 1974-75 winter season demonstrated the ability of this system to provide all-weather ice information to shippers in a timely manner