scholarly journals توظیف أسلوبی التحلیل العنقودی والتحلیل التمییزی فی تصنیف البیانات وبناء الدوال التمییزیة Employing the two methods of Cluster Analysis and Discriminant Analysis in Data Classification and building discriminative functions.

2020 ◽  
Vol 39 (1) ◽  
pp. 11-39
Author(s):  
محمد موسى الشمرانی
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Data Classification ◽  
Discriminative Functions

Classifying the Past: Discriminant Analysis and its Application to Medieval Farming Systems

1996 ◽  
Vol 8 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Ken Bartley
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Processing Time ◽  
Farming Systems ◽  
Frame Of Reference ◽  
Analytical Models ◽  
Successful Implementation ◽  
Medieval Period ◽  
The Past ◽  
Livestock Management

This paper discusses the need for nationally based analytical models of the medieval period. The use of cluster analysis as a method for classifying demesne farms, by the crops they grew and their livestock management, is explained. Successful implementation of cluster analysis requires both the existence of a large base sample, to permit isolation of specific groupings within the data, and access to considerable processing time. The paper concludes by demonstrating how discriminant analysis can provide an efficient and systematic way of classifying even a single manor within a national frame of reference.

Multivariate consumption profiling (MCP) for intelligent meter systems: a methodology to define categories and levels

2010 ◽  
Vol 10 (5) ◽  
pp. 710-720 ◽  
Author(s):  
J. L. Solanas ◽  
M. R. Cussó
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Multivariate Analysis ◽  
Discriminant Analysis ◽  
Reference Population ◽  
Statistical Analyses ◽  
Conceptual Schema ◽  
Data Variability ◽  
Water Companies ◽  
Analyse Data

Multivariate Consumption Profiling (MCP) is a methodology to analyse the readings made by Intelligent Meter (IM) systems. Even in advanced water companies with well supported IM, full statistical analyses are not performed, since no efficient methods are available to deal with all the data items. Multivariate Analysis has been proposed as a convenient way to synthesise all IM information. MCP uses Factor Analysis, Cluster Analysis and Discriminant Analysis to analyse data variability by categories and levels, in a cyclical improvement process. MCP obtains a conceptual schema of a reference population on a set of classifying tables, one for each category. These tables are quantitative concepts to evaluate consumption, meter sizing, leakage and undermetering for populations and groupings and individual cases. They give structuring items to enhance “traditional” statistics. All the relevant data from each new meter reading can be matched to the classifying tables. A set of indexes is computed and thresholds are used to select those cases with the desired profiles. The paper gives an example of a MCP conceptual schema for five categories, three variables, and five levels, and obtains its classifying tables. It shows the use of case profiles to implement actions in accordance with the operative objectives.

Effect of Topography on Maize Grains Elemental Profile: A Chemometric Approach

2020 ◽  
Vol 16 (8) ◽  
pp. 1079-1087
Author(s):  
Jorgelina Z. Heredia ◽  
Carlos A. Moldes ◽  
Raúl A. Gil ◽  
José M. Camiña
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Microwave Plasma ◽  
Emission Spectrometry ◽  
Linear Discriminant ◽  
Maize Seeds ◽  
Elemental Profile ◽  
Mineral Profile ◽  
Topographic Characteristics

Background: The elemental composition of maize grains depends on the soil, land and environment characteristics where the crop grows. These effects are important to evaluate the availability of nutrients with complex dynamics, such as the concentration of macro and micronutrients in soils, which can vary according to different topographies. There is available scarce information about the influence of topographic characteristics (upland and lowland) where culture is developed with the mineral composition of crop products, in the present case, maize seeds. On the other hand, the study of the topographic effect on crops using multivariate analysis tools has not been reported. Objective: This paper assesses the effect of topographic conditions on plants, analyzing the mineral profiles in maize seeds obtained in two land conditions: uplands and lowlands. Materials and Methods: The mineral profile was studied by microwave plasma atomic emission spectrometry. Samples were collected from lowlands and uplands of cultivable lands of the north-east of La Pampa province, Argentina. Results: Differentiation of maize seeds collected from both topographical areas was achieved by principal components analysis (PCA), cluster analysis (CA) and linear discriminant analysis (LDA). PCA model based on mineral profile allowed to differentiate seeds from upland and lowlands by the influence of Cr and Mg variables. A significant accumulation of Cr and Mg in seeds from lowlands was observed. Cluster analysis confirmed such grouping but also, linear discriminant analysis achieved a correct classification of both the crops, showing the effect of topography on elemental profile. Conclusions: Multi-elemental analysis combined with chemometric tools proved useful to assess the effect of topographic characteristics on crops.

scholarly journals ECOLOGICAL AND FUNCTIONAL CLUSTERING OF FORESTAL SPECIES IN THE SOUTH WESTERN AMAZONIA

2016 ◽  
Vol 40 (6) ◽  
pp. 1083-1090
Author(s):  
Elias Lourenço Vasconcelos Neto ◽  
Celso Azevedo ◽  
Luciano Ribas ◽  
Marcus Neves d'Oliveira
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Tree Species ◽  
Permanent Plots ◽  
Cumulative Frequency ◽  
Cumulative Frequency Distribution ◽  
Functional Clustering ◽  
Breast Height ◽  
Three Stages ◽  
Species Grouping

ABSTRACT The aim of this study was to perform ecological and functional clustering of tree species in southwestern Amazon. Developed from data from 95 permanent plots of 1 ha each, all individuals with diameter at breast height (DBH) ≥10 cm were measured. The species grouping was performed in three stages: (1) cluster analysis, using the variables: diameter annual periodic increment -(IPADAP) considering three competition levels (high, medium and low) and the 95th percentile of the diameters (P95) cumulative frequency distribution (Ward hierarchical method); (2) Discriminant analysis, using the variables P95 and IPADAP by Fisher's method and (3) subjective stage, considering the species ecological characteristics. The Ward and Fisher methods used for discriminant and cluster analyses were effective for species grouping resulting on the formation of 10 groups. Variables: IPADAP and and P95 were efficient on the formed groups discrimination.. Variations in the growth rates for the overall mean data were reduced wen calculated for each group of species.

A taxonomy of the scope and organization of local sexually transmitted disease services for policy and practice

2018 ◽  
Vol 29 (14) ◽  
pp. 1375-1383
Author(s):  
Hector P Rodriguez ◽  
Summer Starling ◽  
Zosha Kandel ◽  
Robert Weech-Maldonado ◽  
Nicholas J Moss ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Critical Role ◽  
Transmitted Disease ◽  
The United States ◽  
Incidence Rates ◽  
Contact Tracing ◽  
Cluster Solution ◽  
Local Health ◽  
Sexually Transmitted

Local health departments (LHDs) and their organizational partners play a critical role in controlling sexually transmitted diseases (STDs) in the United States. We examine variation in the differentiation, integration, and concentration (DIC) of STD services and develop a taxonomy describing the scope and organization of local STD services. LHD STD programs (n = 115) in Alabama (AL) and California (CA) responded to surveys assessing STD services available in 2014. K-means cluster analysis identified LHD groupings based on DIC variation. Discriminant analysis validated cluster solutions. Differences in organizational partnerships and scope of STD services were compared by taxonomy category. Multivariable regression models estimated the association of the STD services organization taxonomy and five-year (2010–2014) gonorrhea incidence rates, controlling for county-level sociodemographics and resources. A three-cluster solution was identified: (1) low DIC (n = 74), (2) moderate DIC (n = 31), and (3) high DIC (n = 10). In discriminant analysis, 95% of jurisdictions were classified into the same types as originally assigned through K-means cluster analysis. High DIC jurisdictions were more likely (p < 0.001) to partner with most organizations than moderate and low DIC jurisdictions, and more likely (p < 0.001) to conduct STD needs assessment, comprehensive sex education, and targeted screening. In contrast, contact tracing, case management, and investigations were conducted similarly across jurisdictions. In adjusted analyses, there were no differences in gonorrhea incidence rates by category. Jurisdictions in CA and AL can be characterized into three distinct clusters based on the DIC of STD services. Taxonomic analyses may aid in improving the reach and effectiveness of STD services.

scholarly journals SPECIES COMPOSITION OF FRESHWATER EELS (Anguilla spp.) IN EIGHT RIVERS FLOWING TO PALABUHANRATU BAY, SUKABUMI, INDONESIA

2016 ◽  
Vol 7 (2) ◽  
Author(s):  
Agus Alim Hakim ◽  
M Mukhlis Kamal ◽  
Nurlisa A Butet ◽  
Ridwan Affandi
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Species Composition ◽  
Dominant Species ◽  
Morphological Identification ◽  
Morphometric Data ◽  
Freshwater Eel ◽  
Glass Eels ◽  
Freshwater Eels ◽  
Tropical Freshwater

Freshwater eel (Anguilla spp.) is a catadromus fish that migrates from freshwater into seawater for spawning and return to freshwater during larvae stage to grow. The objective of this study was to determine species composition of tropical freshwater eels based on morphology collected from several rivers flowing in to the Palabuhan Ratu Bay. Young, adult, and glass eels were caught in August 2014 until Desember 2014. Glass eels were only caught in Cimandiri River. Freshwater eels were classified by ano-dorsal length (AD) divided by total length (TL), cluster analysis, and discriminant analysis based on morphometric data. The results showed different AD/TL of young and adult, i.e., 1.93±0.51 for A. bicolor bicolor, and 16.99±0.65 for A. marmorata, and three different AD/TL of glass eels i.e.,1.72±1.05 for A. bicolor bicolor6.60±1.79 for A. nebulosa nebulosa, and 15.07±1.04 for A. marmorata. Cluster analysis showed three groups of population  characters of young and adult eels i.e.  A. bicolor bicolor (2 groups) and A. marmorata (1 group). Discriminant analysis showed three groups of glass eels population i.e., A. bicolor bicolor, A. nebulosa nebulosa, and A. marmorata. Morphological identification showed that young and adult eels in Cibareno  and Citepus rivers had two species i.e., A. bicolor bicolor and A. marmorata. Glass eels from Cimandiri river had three species i.e., A. bicolorbicolor, A. nebulosanebulosa, and A. marmorata. A. bicolor bicolor was found in each rivers and as a dominant species in Palabuhan Ratu Bay.Keywords: A. bicolor bicolor, A. marmorata, A. nebulosa nebulosa, species composition

scholarly journals Ultraviolet Spectroscopy Used to Fingerprint Five Wild-Grown Edible Mushrooms (Boletaceae) Collected from Yunnan, China

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Yan Li ◽  
Ji Zhang ◽  
Tao Li ◽  
Tianwei Yang ◽  
Yuanzhong Wang ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Hierarchical Cluster Analysis ◽  
Visual Discrimination ◽  
Uv Spectroscopy ◽  
Hierarchical Cluster ◽  
Uv Spectra ◽  
Edible Mushrooms ◽  
Ultraviolet Spectroscopy

Nowadays, wild-grown edible mushrooms which are natural, nutritious, and healthy get more and more popular by large consumers. In this paper, UV spectra of different Boletaceae mushrooms with the aid of partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were shown to be a practical and rapid method for discrimination purpose. The specimens of Boletus edulis, Boletus ferrugineus, Boletus tomentipes, Leccinum rugosiceps, and Xerocomus sp. were described based on the UV spectra. From the results, all the specimens were characterized by strong absorption at the wavelengths of 274 and 284 nm and showed the shoulder at 296 nm. However, changes could be seen in the peak heights at the same wavelength for different samples. After analyzing by chemometrics, visual discrimination among samples was presented and the relationships among them were also obtained. This study showed that UV spectroscopy combined with chemometrics methods could be used successfully as a simple and effective approach for characterization of these five wild-grown edible mushrooms at species and genus levels. Meanwhile, this rapid and simple methodology could also provide reference for the discrimination of edible mushrooms.

scholarly journals Second Version of a Mini-Survey to Evaluate Food Intake Quality (Mini-ECCA v.2): Reproducibility and Ability to Identify Dietary Patterns in University Students

Nutrients ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 809
Author(s):  
María Fernanda Bernal-Orozco ◽  
Patricia Belen Salmeron-Curiel ◽  
Ruth Jackelyne Prado-Arriaga ◽  
Jaime Fernando Orozco-Gutiérrez ◽  
Nayeli Badillo-Camacho ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Food Intake ◽  
University Students ◽  
Excellent Agreement ◽  
Dietary Patterns ◽  
Weighted Kappa ◽  
Health Science ◽  
Sweetened Beverages ◽  
Group 2

Evaluation of food intake quality using validated tools makes it possible to give individuals or populations recommendations for improving their diet. This study’s objective was to evaluate the reproducibility and ability to identify dietary patterns of the second version of the Mini Food Intake Quality Survey (Mini-ECCA v.2). The survey was administered using a remote voting system on two occasions with four-week intervals between administrations to 276 health science students (average age = 20.1 ± 3.1 years; 68% women). We then performed a per-question weighted kappa calculation, a cluster analysis, an ANOVA test by questionnaire item and between identified clusters, and a discriminant analysis. Moderate to excellent agreement was observed (weighted κ = 0.422–0.662). The cluster analysis identified three groups, and the discriminant analysis obtained three classification functions (85.9% of cases were correctly classified): group 1 (19.9%) was characterized by higher intake of water, vegetables, fruit, fats, oilseeds/avocado, meat and legumes (healthy food intake); group 2 (47.1%) frequently consumed both fish and unhealthy fats (habits in need of improvement); group 3 (33%) frequently consumed sweetened beverages, foods not prepared at home, processed foods, refined cereals and alcohol (unhealthy food intake). In conclusion, the Mini-ECCA v.2 has moderate to excellent agreement, and it is able to identify dietary patterns in university students.

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