Search results for " discriminant analysis"
showing 10 items of 179 documents
Linear vs. non-linear classification of winners, drawers and losers at FIFA World Cup 2014
2017
Purpose: Tactical analyses to distinguish between football teams that were more or less successful have been conducted up to now only by means of linear methods (like discriminant analysis). Concer...
Cultivable microorganisms associated with honeys of different geographical and botanical origin
2014
In this study, the composition of the cultivable microbial populations of 38 nectar honey and honeydew honey samples of different botanical and geographical origin were assessed. After growth in specific media, various colonies with different appearance were isolated and purified before phenotypic (morphological, physiological and biochemical traits) and genotypic [randomly amplified polymorphic DNA (RAPD), repetitive DNA elements-PCR (rep-PCR) and restriction fragment length polymorphism (RFLP)] differentiation. The identification was carried out by 16S rRNA gene sequencing for bacteria and, in addition to RFLP, by sequencing the D1/D2 region of the 26S rRNA gene for yeasts and the 5.8S-IT…
A chromatochemometric approach for evaluating and selecting the perfume maceration time.
2010
Abstract A chemometric treatment of the data obtained by gas chromatography (GC) with flame ionization detector (FID) has been proposed to study the maceration time involved in perfumes manufacture with the final purpose of reducing this time but preserving the organoleptic characteristics of the perfume that is being elaborated. In this sense, GC–FID chromatograms were used as a fingerprint of perfume samples subjected to different maceration times, and data were treated by linear discriminant analysis (LDA), by comparing to a set of samples known to be macerated or not, which were used as calibration objects. The GC–FID methodology combined with the treatment of data by LDA has been appli…
Varietal and geographic classification of french red wines in terms of pigments and flavonoid compounds
1988
Thirty-four French red wines originating from six different grape varieties and three different production areas were analysed in duplicate for 15 anthocyanins, ten flavonoids and three colour parameters, F-statistics, principal component analysis and stepwise discriminant analysis were used to identify and to explain differences among samples. Clear difference between wines made from different varieties were mainly related to anthocyanin 3-acylglucosides. Malvidin and peonidin 3-acetylglucosides were found in increasing concentrations in wines made respectively from Grenache, Carignan, Cinsault, Merlot, Carbernet Sauvignon and Cabernet Franc grapes; the concentrations of peonidin and malvi…
Chemical Element Levels as a Methodological Tool in Forensic Science
2014
The aim of the present study was to define a methodological strategy for understanding how post- mortem degradation in bones caused by the environment affects different skeletal parts and for selecting better preserved bone samples, employing rare earth elements (REEs) analysis and multivariate statistics. To test our methodological proposal the samples selected belong to adult and young individuals and were obtained from the Late Roman Necropolis of c/Virgen de la Misericordia located in Valencia city centre (Comunidad Valenciana, Spain). Therefore, a method for the determination of major elements, trace elements and REEs in bone remains has been developed employing Inductively-Coupled Pla…
Incremental Gaussian Discriminant Analysis based on Graybill and Deal weighted combination of estimators for brain tumour diagnosis
2011
In the last decade, machine learning (ML) techniques have been used for developing classifiers for automatic brain tumour diagnosis. However, the development of these ML models rely on a unique training set and learning stops once this set has been processed. Training these classifiers requires a representative amount of data, but the gathering, preprocess, and validation of samples is expensive and time-consuming. Therefore, for a classical, non-incremental approach to ML, it is necessary to wait long enough to collect all the required data. In contrast, an incremental learning approach may allow us to build an initial classifier with a smaller number of samples and update it incrementally…
SIMULATION EXPERIMENTS WITH MULTIPLE GROUP LINEAR AND QUADRATIC DISCRIMINANT ANALYSIS
1973
Summary A simulation program is described which can be performed to obtain estimates of the different types of misclassification probabilities for multiple group linear and quadratic discriminant analysis. The program can be used to study how these errors depend on sample sizes and the different parameters of the multivariate normal distribution. Examples for several simulation experiments are given and possible conclusions are discussed.
Comparative Study of Several Machine Learning Algorithms for Classification of Unifloral Honeys
2021
Unifloral honeys are highly demanded by honey consumers, especially in Europe. To ensure that a honey belongs to a very appreciated botanical class, the classical methodology is palynological analysis to identify and count pollen grains. Highly trained personnel are needed to perform this task, which complicates the characterization of honey botanical origins. Organoleptic assessment of honey by expert personnel helps to confirm such classification. In this study, the ability of different machine learning (ML) algorithms to correctly classify seven types of Spanish honeys of single botanical origins (rosemary, citrus, lavender, sunflower, eucalyptus, heather and forest honeydew) was investi…
ChemInform Abstract: Antimicrobial Activity Characterization in a Heterogeneous Group of Compounds.
2010
In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds. The structural descriptors utilized are the topological connectivity indexes. The methods followed are stepwise linear discriminant analysis (linear analysis) and artificial neural network (nonlinear analysis). Although both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network is, in this case, more adequate, since it shows in a test set a prediction success of 98%, versus 92% obtained with linear discriminant analysis.
Antimicrobial Activity Characterization in a Heterogeneous Group of Compounds
1998
In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds. The structural descriptors utilized are the topological connectivity indexes. The methods followed are stepwise linear discriminant analysis (linear analysis) and artificial neural network (nonlinear analysis). Although both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network is, in this case, more adequate, since it shows in a test set a prediction success of 98%, versus 92% obtained with linear discriminant analysis.