A systematic comparison of supervised classifiers

Pattern recognition techniques have been employed in a myriad of industrial, medical, commercial and academic applications. To tackle such a diversity of data, many techniques have been devised. However, despite the long tradition of pattern recognition research, there is no technique that yields the best classification in all scenarios. Therefore, the consideration of as many as possible techniques presents itself as an fundamental practice in applications aiming at high accuracy. Typical works comparing methods either emphasize the performance of a given algorithm in validation tests or systematically compare various algorithms, assuming that the practical use of these methods is done by experts. In many occasions, however, researchers have to deal with their practical classification tasks without an in-depth knowledge about the underlying mechanisms behind parameters. Actually, the adequate choice of classifiers and parameters alike in such practical circumstances constitutes a long-standing problem and is the subject of the current paper. We carried out a study on the performance of nine well-known classifiers implemented by the Weka framework and compared the dependence of the accuracy with their configuration parameter configurations. The analysis of performance with default parameters revealed that the k-nearest neighbors method exceeds by a large margin the other methods when high dimensional datasets are considered. When other configuration of parameters were allowed, we found that it is possible to improve the quality of SVM in more than 20% even if parameters are set randomly. Taken together, the investigation conducted in this paper suggests that, apart from the SVM implementation, Weka's default configuration of parameters provides an performance close the one achieved with the optimal configuration

Determining the Surface-To-Bulk Progression in the Normal-State Electronic Structure of Sr2RuO4 by Angle-Resolved Photoemission and Density Functional Theory

In search of the potential realization of novel normal-state phases on the surface of Sr2RuO4 - those stemming from either topological bulk properties or the interplay between spin-orbit coupling (SO) and the broken symmetry of the surface - we revisit the electronic structure of the top-most layers by ARPES with improved data quality as well as ab-initio LDA slab calculations. We find that the current model of a single surface layer (\surd2x\surd2)R45{\deg} reconstruction does not explain all detected features. The observed depth-dependent signal degradation, together with the close quantitative agreement with LDA+SO slab calculations based on the LEED-determined surface crystal structure, reveal that (at a minimum) the sub-surface layer also undergoes a similar although weaker reconstruction. This points to a surface-to-bulk progression of the electronic states driven by structural instabilities, with no evidence for Dirac and Rashba-type states or surface magnetism.Comment: 4 pages, 4 figures, 1 table. Further information and PDF available at: http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/articles.htm

Na2IrO3 as a spin-orbit-assisted antiferromagnetic insulator with a 340 meV gap

We study Na2IrO3 by ARPES, optics, and band structure calculations in the local-density approximation (LDA). The weak dispersion of the Ir 5d-t2g manifold highlights the importance of structural distortions and spin-orbit coupling (SO) in driving the system closer to a Mott transition. We detect an insulating gap {\Delta}_gap = 340 meV which, at variance with a Slater-type description, is already open at 300 K and does not show significant temperature dependence even across T_N ~ 15 K. An LDA analysis with the inclusion of SO and Coulomb repulsion U reveals that, while the prodromes of an underlying insulating state are already found in LDA+SO, the correct gap magnitude can only be reproduced by LDA+SO+U, with U = 3 eV. This establishes Na2IrO3 as a novel type of Mott-like correlated insulator in which Coulomb and relativistic effects have to be treated on an equal footing.Comment: Accepted in Physical Review Letters. Auxiliary and related material can be found at: http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/articles.htm

Correlations between climate network and relief data

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Correlations between climate network and relief data

Peer reviewedPublisher PD

Rashba spin-splitting control at the surface of the topological insulator Bi2Se3

The electronic structure of Bi2Se3 is studied by angle-resolved photoemission and density functional theory. We show that the instability of the surface electronic properties, observed even in ultra-high-vacuum conditions, can be overcome via in-situ potassium deposition. In addition to accurately setting the carrier concentration, new Rashba-like spin-polarized states are induced, with a tunable, reversible, and highly stable spin splitting. Ab-initio slab calculations reveal that these Rashba state are derived from the 5QL quantum-well states. While the K-induced potential gradient enhances the spin splitting, this might be already present for pristine surfaces due to the symmetry breaking of the vacuum-solid interface.Comment: A high-resolution version can be found at http://www.physics.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Articles/BiSe_K.pd

Accuracy of genomic prediction for tick resistance in Braford and Hereford cattle.

This work aimed to determine the accuracy and bias of genomic predictions of Braford (BO) and Hereford (HH) cattle genetic resistance to ticks