Orthogonal-least-squares regression: A unified approach for data modelling

A unified approach is proposed for data modelling that includes supervised regression and classification applications as well as unsupervised probability density function estimation. The orthogonal-least-squares regression based on the leave-one-out test criteria is formulated within this unified data-modelling framework to construct sparse kernel models that generalise well. Examples from regression, classification and density estimation applications are used to illustrate the effectiveness of this generic data-modelling approach for constructing parsimonious kernel models with excellent generalisation capability. (C) 2008 Elsevier B.V. All rights reserved.

Kernel classifier construction using orthogonal forward selection and boosting with Fisher ratio class separability measure

A greedy technique is proposed to construct parsimonious kernel classifiers using the orthogonal forward selection method and boosting based on Fisher ratio for class separability measure. Unlike most kernel classification methods, which restrict kernel means to the training input data and use a fixed common variance for all the kernel terms, the proposed technique can tune both the mean vector and diagonal covariance matrix of individual kernel by incrementally maximizing Fisher ratio for class separability measure. An efficient weighted optimization method is developed based on boosting to append kernels one by one in an orthogonal forward selection procedure. Experimental results obtained using this construction technique demonstrate that it offers a viable alternative to the existing state-of-the-art kernel modeling methods for constructing sparse Gaussian radial basis function network classifiers. that generalize well.

M-estimator, and D-optimality model construction using orthogonal forward regression

This correspondence introduces a new orthogonal forward regression (OFR) model identification algorithm using D-optimality for model structure selection and is based on an M-estimators of parameter estimates. M-estimator is a classical robust parameter estimation technique to tackle bad data conditions such as outliers. Computationally, The M-estimator can be derived using an iterative reweighted least squares (IRLS) algorithm. D-optimality is a model structure robustness criterion in experimental design to tackle ill-conditioning in model Structure. The orthogonal forward regression (OFR), often based on the modified Gram-Schmidt procedure, is an efficient method incorporating structure selection and parameter estimation simultaneously. The basic idea of the proposed approach is to incorporate an IRLS inner loop into the modified Gram-Schmidt procedure. In this manner, the OFR algorithm for parsimonious model structure determination is extended to bad data conditions with improved performance via the derivation of parameter M-estimators with inherent robustness to outliers. Numerical examples are included to demonstrate the effectiveness of the proposed algorithm.

Fast kernel classifier construction using orthogonal forward selection to minimise leave-one-out misclassification rate

We propose a simple yet computationally efficient construction algorithm for two-class kernel classifiers. In order to optimise classifier's generalisation capability, an orthogonal forward selection procedure is used to select kernels one by one by minimising the leave-one-out (LOO) misclassification rate directly. It is shown that the computation of the LOO misclassification rate is very efficient owing to orthogonalisation. Examples are used to demonstrate that the proposed algorithm is a viable alternative to construct sparse two-class kernel classifiers in terms of performance and computational efficiency.

A bagging-based correction for the mixture model estimator of population size

Estimation of a population size by means of capture-recapture techniques is an important problem occurring in many areas of life and social sciences. We consider the frequencies of frequencies situation, where a count variable is used to summarize how often a unit has been identified in the target population of interest. The distribution of this count variable is zero-truncated since zero identifications do not occur in the sample. As an application we consider the surveillance of scrapie in Great Britain. In this case study holdings with scrapie that are not identified (zero counts) do not enter the surveillance database. The count variable of interest is the number of scrapie cases per holding. For count distributions a common model is the Poisson distribution and, to adjust for potential heterogeneity, a discrete mixture of Poisson distributions is used. Mixtures of Poissons usually provide an excellent fit as will be demonstrated in the application of interest. However, as it has been recently demonstrated, mixtures also suffer under the so-called boundary problem, resulting in overestimation of population size. It is suggested here to select the mixture model on the basis of the Bayesian Information Criterion. This strategy is further refined by employing a bagging procedure leading to a series of estimates of population size. Using the median of this series, highly influential size estimates are avoided. In limited simulation studies it is shown that the procedure leads to estimates with remarkable small bias.

Low-lying excited states and primary photoproducts of [Os-3(CO)(10)-(s-cis-L)] (L = cyclohexa-1,3-diene, buta-1,3-diene)] clusters studied by picosecond time-resolved UV/Vis and IR spectroscopy and by density functional theory

Combined picosecond transient absorption and time-resolved infrared studies were performed, aimed at characterising low-lying excited states of the cluster [Os-3(CO)(10)(s-cis-L)] (L= cyclohexa-1,3-diene, 1) and monitoring the formation of its photoproducts. Theoretical (DFT and TD-DFT) calculations on the closely related cluster with L=buta-1,3-diene (2') have revealed that the low-lying electronic transitions of these [Os-3(CO)(10)(s-cis-1,3-diene)] clusters have a predominant sigma(core)pi*(CO) character. From the lowest sigmapi* excited state, cluster 1 undergoes fast Os-Os(1,3-diene) bond cleavage (tau=3.3 ps) resulting in the formation of a coordinatively unsaturated primary photoproduct (1a) with a single CO bridge. A new insight into the structure of the transient has been obtained by DFT calculations. The cleaved Os-Os(1,3-diene) bond is bridged by the donor 1,3-diene ligand, compensating for the electron deficiency at the neighbouring Os centre. Because of the unequal distribution of the electron density in transient la, a second CO bridge is formed in 20 ps in the photoproduct [Os-3(CO)(8)(mu-CO)(2)- (cyclohexa-1,3-diene)] (1b). The latter compound, absorbing strongly around 630 nm, mainly regenerates the parent cluster with a lifetime of about 100 ns in hexane. Its structure, as suggested by the DFT calculations, again contains the 1,3-diene ligand coordinated in a bridging fashion. Photoproduct 1b can therefore be assigned as a high-energy coordination isomer of the parent cluster with all Os-Os bonds bridged.

Strongly nucleophilic RhI centre in square-planar complexes with terdentate (κ3) 2,2′:6′,2′′-terpyridine ligands: crystallographic, electrochemical and density functional theoretical studies

Rh-I-terpyridine complexes have been unambiguously formed for the first time. The 2,21:6',2"-terpyridine (tpy), 4'-chloro-2,2':6',2"-terpyridine (4'-Cl-tpy) and 4'-(tert-butyldimethylsilyl-ortho-carboranyl)-2,2':6',2"-terpyridine (carboranyl-tpy) ligands were used for successful syntheses and characterisation of the corresponding Rh-I complexes with halide coligands, [Rh(X)(4'-Y-terpyridine)] (X = Cl, Y = H, Cl, carboranyl; X = Br, Y = H). All four neutral Rh-tpy complexes are square planar, with Rh-X bonds in the plane of the 4'-Y-terpyridine ligands. Full characterisation of these dark blue, highly air-sensitive compounds was hampered by their poor solubility in various organic solvents. This is mainly due to the formation of pi-stacked aggregates, as evidenced by the crystal structure of [Rh(Cl)(tpy)]; in addition, [Rh(Cl)(carboranyl-tpy)] merely forms discrete dimers. The (bonding) properties of the novel Rh-I-terpyridine complexes have been studied with single-crystal X-ray diffraction, (time-dependent) density functional theoretical (DFT) calculations, far-infrared spectroscopy, electronic absorption spectroscopy and cyclic voltammetry. From DFT calculations, the HOMO of the studied Rh-I-terpyridine complexes involves predominantly the metal centre, while the LUMO resides on the terpyridine ligand. Absorption bands of the studied complexes in the visible region (400-900 nm) can be assigned to MLCT and MLCT/XLCT transitions. The relatively low oxidation potentials of [Rh(X)(tpy)] (X = Cl, Br) point to a high electron density on the metal centre. This makes the Rh-I-terpyridine complexes strongly nucleophilic and (potentially) highly reactive towards various (small) substrate molecules containing carbon-halide bonds.

Minimum neighbour and extended Kalman filter estimator: a practical distributed channel assignment scheme for dense wireless local area networks

Dense deployments of wireless local area networks (WLANs) are becoming a norm in many cities around the world. However, increased interference and traffic demands can severely limit the aggregate throughput achievable unless an effective channel assignment scheme is used. In this work, a simple and effective distributed channel assignment (DCA) scheme is proposed. It is shown that in order to maximise throughput, each access point (AP) simply chooses the channel with the minimum number of active neighbour nodes (i.e. nodes associated with neighbouring APs that have packets to send). However, application of such a scheme to practice depends critically on its ability to estimate the number of neighbour nodes in each channel, for which no practical estimator has been proposed before. In view of this, an extended Kalman filter (EKF) estimator and an estimate of the number of nodes by AP are proposed. These not only provide fast and accurate estimates but can also exploit channel switching information of neighbouring APs. Extensive packet level simulation results show that the proposed minimum neighbour and EKF estimator (MINEK) scheme is highly scalable and can provide significant throughput improvement over other channel assignment schemes.

Inter-relationships between small, dense low-density lipoprotein (LDL), plasma triacylglycerol and LDL apoprotein B in an atherogenic lipoprotein phenotype in free-living subjects

A predominance of small, dense low-density lipoprotein (LDL) is a major component of an atherogenic lipoprotein phenotype, and a common, but modifiable, source of increased risk for coronary heart disease in the free-living population. While much of the atherogenicity of small, dense LDL is known to arise from its structural properties, the extent to which an increase in the number of small, dense LDL particles (hyper-apoprotein B) contributes to this risk of coronary heart disease is currently unknown. This study reports a method for the recruitment of free-living individuals with an atherogenic lipoprotein phenotype for a fish-oil intervention trial, and critically evaluates the relationship between LDL particle number and the predominance of small, dense LDL. In this group, volunteers were selected through local general practices on the basis of a moderately raised plasma triacylglycerol (triglyceride) level (>1.5 mmol/l) and a low concentration of high-density-lipoprotein cholesterol (<1.1 mmol/l). The screening of LDL subclasses revealed a predominance of small, dense LDL (LDL subclass pattern B) in 62% of the cohort. As expected, subjects with LDL subclass pattern B were characterized by higher plasma triacylglycerol and lower high-density lipoprotein cholesterol (<1.1 mmol/l) levels and, less predictably, by lower LDL cholesterol and apoprotein B levels (P<0.05; LDL subclass A compared with subclass B). While hyper-apoprotein B was detected in only five subjects, the relative percentage of small, dense LDL-III in subjects with subclass B showed an inverse relationship with LDL apoprotein B (r=-0.57; P<0.001), identifying a subset of individuals with plasma triacylglycerol above 2.5 mmol/l and a low concentration of LDL almost exclusively in a small and dense form. These findings indicate that a predominance of small, dense LDL and hyper-apoprotein B do not always co-exist in free-living groups. Moreover, if coronary risk increases with increasing LDL particle number, these results imply that the risk arising from a predominance of small, dense LDL may actually be reduced in certain cases when plasma triacylglycerol exceeds 2.5 mmol/l.