Search results for "linear discriminant analysis"
showing 10 items of 163 documents
Pengembangan Kriteria dan Klasifikasi Tingkat Kekritisan Lahan pada Skala Tinjau di Kawasan Budidaya Pertanian Lahan Kering di Kabupaten Bogor
2018
<em>The objectives of this research are to develop critical land criteria and classification on the reconnaissance scales. The method used in this research is survey method through case studies. Data analysis methods include: bivariate correlation analysis, cluster analysis, and discriminant analysis. The results showed development criteria at reconnaissance scale resulted three determinant variables, namely: effective soil depth, stones, and degree of erosion; and produced two classes of critical land, namely: Critical class and Non-Critical class.</em>
Rapid and Nondestructive Determination of Egg Freshness Category and Marked Date of Lay using Spectral Fingerprint
2020
The potential of nondestructive prediction of egg freshness based on near-infrared (NIR) spectra fingerprints would be beneficial to quality control officers and consumers alike. In this study, handheld NIR spectrometer in the range of 740 nm to 1070 nm and chemometrics were used to simultaneously determine egg freshness based on marked date of lay for eggs stored under cold and ambient conditions. The spectra acquired from the eggs were preprocessed using multiplicative scatter correction and principal component analysis (MSC-PCA). Linear discriminant analysis (LDA) was used to build identification model to predict the category of freshness, while partial least square regression (PLS-R) wa…
Parasite infracommunities as predictors of harvest location of bogue (Boops boops L.): a pilot study using statistical classifiers
2005
The accuracy of classifying bogue (Boops boops) according to the fishery from which it was harvested was evaluated by applying several statistical classification techniques to fish parasite abundances. Bogue captured in 2001 in two fisheries off the Atlantic coast of Spain were compared with one off the Spanish Mediterranean coast. One hundred bogue were classified to each harvest location (fishery) using different numbers of parasite species chosen as predictors by a best subset method. Two parametric methods of classification (linear and quadratic discriminant analysis) were compared with two non-parametric approaches (k-nearest neighbour classification and feed-forward neural network) an…
A Comment on the Coefficient of Determination for Binary Responses
1992
Abstract Linear logistic or probit regression can be closely approximated by an unweighted least squares analysis of the regression linear in the conditional probabilities provided that these probabilities for success and failure are not too extreme. It is shown how this restriction on the probabilities translates into a restriction on the range of the coefficient of determination R 2 so that, as a consequence, R 2 is not suitable to judge the effectiveness of linear regressions with binary responses even if an important relation is present.
STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling
2012
STATIS is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables collected on the same observations, or, alternatively, as in a variant called dual-STATIS, multiple data tables where the same variables are measured on different sets of observations. STATIS proceeds in two steps: First it analyzes the between data table similarity structure and derives from this analysis an optimal set of weights that are used to compute a linear combination of the data tables called the compromise that best represents the information common to the different data tables; Second, the PCA of this compromise gives an optimal map of the observation…
On the usage of joint diagonalization in multivariate statistics
2022
Scatter matrices generalize the covariance matrix and are useful in many multivariate data analysis methods, including well-known principal component analysis (PCA), which is based on the diagonalization of the covariance matrix. The simultaneous diagonalization of two or more scatter matrices goes beyond PCA and is used more and more often. In this paper, we offer an overview of many methods that are based on a joint diagonalization. These methods range from the unsupervised context with invariant coordinate selection and blind source separation, which includes independent component analysis, to the supervised context with discriminant analysis and sliced inverse regression. They also enco…
Large-sample properties of unsupervised estimation of the linear discriminant using projection pursuit
2021
We study the estimation of the linear discriminant with projection pursuit, a method that is unsupervised in the sense that it does not use the class labels in the estimation. Our viewpoint is asymptotic and, as our main contribution, we derive central limit theorems for estimators based on three different projection indices, skewness, kurtosis, and their convex combination. The results show that in each case the limiting covariance matrix is proportional to that of linear discriminant analysis (LDA), a supervised estimator of the discriminant. An extensive comparative study between the asymptotic variances reveals that projection pursuit gets arbitrarily close in efficiency to LDA when the…
Use of linear discriminant analysis applied to vibrational spectroscopy data to characterize commercial varnishes employed for art purposes.
2007
An improvement of methodologies for characterising synthetic resins used in varnishes employed for art purposes has been suggested. Several kinds of standard of the most common polymeric resins (acrylic, vinyl, poly(vinyl alcohol), alkyd, cellulose nitrate, latex, polyester, polyurethane, epoxy, organosilicic, and ketonic) were analyzed by Fourier transform infrared (FTIR) spectroscopy. Synthetic resins characterization is based on the mathematical treatment of their whole spectrum, dividing it in 13 sections, avoiding the one-by-one interpretation of the absorption bands. The mathematical model takes as variables the maximal absorbance of each section, and each synthetic standard resin as …
Time, frequency and information domain analysis of short-term heart rate variability before and after focal and generalized seizures in epileptic chi…
2019
OBJECTIVE In this work we explore the potential of combining standard time and frequency domain indexes with novel information measures, to characterize pre- and post-ictal heart rate variability (HRV) in epileptic children, with the aim of differentiating focal and generalized epilepsy regarding the autonomic control mechanisms. APPROACH We analyze short-term HRV in 37 children suffering from generalized or focal epilepsy, monitored 10 s, 300 s, 600 s and 1800 s both before and after seizure episodes. Nine indexes are computed in time (mean, standard deviation of normal-to-normal intervals, root mean square of the successive differences (RMSSD)), frequency (low-to-high frequency power rati…
Assessing the territorial influence of an Iberian worship site. The chemical characterisation of the terracotta from the Iron Age sanctuary of La Ser…
2017
This paper presents the study of the prestigious terracotta votive figurines from the Iberian Iron Age sanctuary of La Serreta (Alicante province, Spain) composed of 174 items. Portable X-ray fluorescence (PXRF) was used to identify elemental markers that permit us to observe the differences between local and non-local terracotta figurines and furthermore to evaluate the geographical influence of the La Serreta sanctuary using Principal Component Analysis (PCA). The Partial Least Squares Discriminant Analysis (PLSDA) statistical method was also used to classify the figurines of uncertain geographical origin. The resulting groups were related to typological and stylistic groups of figurines …