Search results for "linear discriminant analysis"
showing 10 items of 163 documents
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…
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.
Combining near-infrared illuminants to optimize venous imaging
2007
The first and perhaps most important phase of a surgical procedure is the insertion of an intravenous (IV) catheter. Currently, this is performed manually by trained personnel. In some visions of future operating rooms, however, this process is to be replaced by an automated system. We previously presented work for localizing near-surface veins via near-infrared (NIR) imaging in combination with structured light ranging for surface mapping and robotic guidance. In this paper, we describe experiments to determine the best NIR wavelengths to optimize vein contrast for physiological differences such as skin tone and/or the presence of hair on the arm or wrist surface. For illumination, we empl…
Similarity-Based Virtual Screening to Find Antituberculosis Agents Based on Novel Scaffolds: Design, Syntheses and Pharmacological Assays
2022
A method to identify molecular scaffolds potentially active against the Mycobacterium tuberculosis complex (MTBC) is developed. A set of structurally heterogeneous agents against MTBC was used to obtain a mathematical model based on topological descriptors. This model was statistically validated through a Leave-n-Out test. It successfully discriminated between active or inactive compounds over 86% in database sets. It was also useful to select new potential antituberculosis compounds in external databases. The selection of new substituted pyrimidines, pyrimidones and triazolo[1,5-a]pyrimidines was particularly interesting because these structures could provide new scaffolds in this field. T…
Classification of Spanish Unifloral Honeys by Discriminant Analysis of Electrical Conductivity, Color, Water Content, Sugars, and pH
2001
To ascertain the most discriminant variables for seven types of Spanish commercial unifloral honeys, stepwise discriminant analysis was performed. Fifteen parameters [pH; water content; electrical conductivity; x, y, and L, chromatic coordinates from the CIE-1931 (xyL) color space; fructose; glucose; sucrose; maltose; isomaltose; maltulose; kojibiose; and the fructose/glucose and glucose/water ratios] were considered. The studied honey types were rosemary, citrus, lavender, sunflower, eucalyptus, heather, and forest. The most discriminant variables, as selected by the multivariate program, were electrical conductivity, color (x, y, L), water content, fructose, and sucrose. All sunflower, eu…
Laser-light backscattering imaging for early decay detection in citrus fruit using both a statistical and a physical model
2015
Abstract The early detection of decay caused by fungi in citrus fruit is a primary concern in the post-harvest phase, the automation of this task still being a challenge. This work reports new progress in the automatic detection of early symptoms of decay in citrus fruit after infection with the pathogen Penicillium digitatum using laser-light backscattering imaging. Backscattering images of sound and decaying parts of the surface of oranges cv. ‘Valencia late’ were obtained using laser diode modules emitting at five wavelengths in the visible and near-infrared regions. The images of backscattered light captured by a camera had radial symmetry with respect to the incident point of the laser…
High Performance Liquid Chromatografy-Mass Spectrometry based chemometric characterization of olive oils
2005
In this study the effective discrimination of extra virgin olive oils is described using HPLC-MS, combined with chemometric evaluation. The presented method is simple since the diluted oil sample is directly injected into the system, without any preliminary chemical derivatization or purification step. Separation of diacylglycerols, triacylglycerols and sterols occurs within 20 min and is achieved using an octadecyl-silica column. Detection is performed by positive APCI mass spectrometry which provided sensitivity to detect over 50 compounds in the sample. After extraction of data, stepwise discriminant function analysis is used to select the variables with the highest discriminative power.…
Use of QSAR methods for predicting the chemiluminescent behaviour of organic compounds upon reaction with potassium permanganate in an acid medium
2009
In previous work, molecular connectivity computations were successfully used to predict the chemiluminescent behaviour of organic compounds upon reaction with common strong oxidants and the native fluorescence too; both of them in a liquid phase. The obtained results were used to develop new analytical procedures to the given compounds. For the first time, connectivity methods were used for a purely analytical purpose. In this work, we went deeper into the knowledge of direct chemiluminescence processes by using molecular connectivity in the form of QSAR methods to predict the chemiluminescence intensity produced by reactions between organic compounds (pharmaceuticals mainly) and potassium …