Search results for "k-nearest neighbors algorithm"
showing 10 items of 52 documents
Mutual nonlinear prediction as a tool to evaluate coupling strength and directionality in bivariate time series: Comparison among different strategie…
2008
We compare the different existing strategies of mutual nonlinear prediction regarding their ability to assess the coupling strength and directionality of the interactions in bivariate time series. Under the common framework of $k$-nearest neighbor local linear prediction, we test three approaches based on cross prediction, mixed prediction, and predictability improvement. The measures of interdependence provided by these approaches are first evaluated on short realizations of bivariate time series generated by coupled Henon models, investigating also the effects of noise. The usefulness of the three mutual nonlinear prediction schemes is then assessed in a common physiological application d…
Quantifying the complexity of short-term heart period variability through K nearest neighbor local linear prediction
2008
The complexity of short-term heart period (HP) variability was quantified exploiting the paradigm that associates the degree of unpredictability of a time series to its dynamical complexity. Complexity was assessed through k-nearest neighbor local linear prediction. A proper selection of the parameter k allowed us to perform either linear or nonlinear prediction, and the comparison of the two approaches to infer the presence of nonlinear dynamics. The method was validated on simulations reproducing linear and nonlinear time series with varying levels of predictability. It was then applied to HP variability series measured from healthy subjects during head-up tilt test, showing that short-te…
An Online Metric Learning Approach through Margin Maximization
2011
This work introduces a method based on learning similarity measures between pairs of objects in any representation space that allows to develop convenient recognition algorithms. The problem is formulated through margin maximization over distance values so that it can discriminate between similar (intra-class) and dissimilar (inter-class) elements without enforcing positive definiteness of the metric matrix as in most competing approaches. A passive-aggressive approach has been adopted to carry out the corresponding optimization procedure. The proposed approach has been empirically compared to state of the art metric learning on several publicly available databases showing its potential bot…
An efficient prototype merging strategy for the condensed 1-NN rule through class-conditional hierarchical clustering
2002
Abstract A generalized prototype-based classification scheme founded on hierarchical clustering is proposed. The basic idea is to obtain a condensed 1-NN classification rule by merging the two same-class nearest clusters, provided that the set of cluster representatives correctly classifies all the original points. Apart from the quality of the obtained sets and its flexibility which comes from the fact that different intercluster measures and criteria can be used, the proposed scheme includes a very efficient four-stage procedure which conveniently exploits geometric cluster properties to decide about each possible merge. Empirical results demonstrate the merits of the proposed algorithm t…
Delineation of Malignant Skin Tumors by Hyperspectral Imaging
2018
This chapter outlines a new non-invasive method for delineation of skin lesions such as lentigo maligna and lentigo maligna melanoma. The method is based on the analysis of hyperspectral (HS) images taken in vivo before surgical excision of the lesions. For this, characteristic features of the spectral signatures of diseased pixels and healthy pixels are extracted, which combine the intensities in a few selected wavebands with the coefficients of the wavelet frame transforms of the spectral curves. To reduce dimensionality and to reveal the internal structure of the datasets, the diffusion maps (DM) technique is applied. The averaged Nearest Neighbor and the Classification and Regression Tr…
Phase transition shifts in films
1991
Abstract We present a Monte Carlo computer simulation study of phase transitions in a three-dimensional Ising/lattice gas model with nearest neighbor attractive coupling and confined to a slit-like capillary with absorbing walls. Data are generated for thicknesses D ⩽ 40 and are used to study the shift of the phase boundaries due to finite wall separation.
Phase Transitions in the Multicomponent Widom-Rowlinson Model and in Hard Cubes on the BCC--Lattice
1997
We use Monte Carlo techniques and analytical methods to study the phase diagram of the M--component Widom-Rowlinson model on the bcc-lattice: there are M species all with the same fugacity z and a nearest neighbor hard core exclusion between unlike particles. Simulations show that for M greater or equal 3 there is a ``crystal phase'' for z lying between z_c(M) and z_d(M) while for z > z_d(M) there are M demixed phases each consisting mostly of one species. For M=2 there is a direct second order transition from the gas phase to the demixed phase while for M greater or equal 3 the transition at z_d(M) appears to be first order putting it in the Potts model universality class. For M large, …
Ab initio Calculations of Bulk and (001) Surface F-centers in ABO3 Perovskites
2021
We analyzed systematic trends in BaTiO 3, SrTiO 3 , PbZrO 3 and SrZrO 3 bulk as well as very rarely performed (001) surface F-center ab initio calculations. The nearest neighbor atomic displacements around the bulk F-center in the ABO 3 perovskites are considerably smaller than the relevant neighbor atomic displacements around the (001) surface $F$ -centers. The $F$ -center electrons are more delocalized for the ABO 3 perovskite (001) surface $F$ -center than for the bulk $F$ -center. Our calculated formation energy differences between the BaTiO 3 , SrTiO 3 , PbZrO 3 and SrZrO 3 bulk and its (001) surface $F$ -centers triggers the $F$ -center segregation from the bulk crystal towards the AB…
Continuous Phase Transitions at Surfaces of CuAu Alloy Models — A Monte Carlo Study of Surface Induced Order and Disorder
1996
The influence of surface on phase transitions has found significant attention in recent years, and a number of excellent reviews exists. [1, 2, 3] A variety of complex phenomena occur which are also related to the physics of adsorption and wetting. The scenario of wetting requires three distinct phases, for instance the vacuum, the bulk phase and a third phase intervening in between at equilibrium. In case of surface induced disorder (SID, a film of disordered layers at the surface “wets” the bulk phase as the temperature approaches the bulk transition temperature T c,b. The transition at the surface may be continuous (standard critical wetting phenomena), and, as theoretically investigated…
Normal and Abnormal Tissue Classification in Positron Emission Tomography Oncological Studies
2018
Positron Emission Tomography (PET) imaging is increasingly used in radiotherapy environment as well as for staging and assessing treatment response. The ability to classify PET tissues, as normal versus abnormal tissues, is crucial for medical analysis and interpretation. For this reason, a system for classifying PET area is implemented and validated. The proposed classification is carried out using k-nearest neighbor (KNN) method with the stratified K-Fold Cross-Validation strategy to enhance the classifier reliability. A dataset of eighty oncological patients are collected for system training and validation. For every patient, lesion (abnormal tissue) and background (normal tissue around …