Discriminant Analysis and Classification

Alkarkhi, Abbas F.M.; Alqaraghuli, Wasin A.A.

doi:10.1016/b978-0-12-814262-2.00010-8

Cited by 12 publications

(9 citation statements)

References 1 publication

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“…The linear discriminant analysis (LDA) (only using training data) was executed to separate classes among the targets evaluated in this study when using the full electromagnetic spectrum. Discriminant analysis, a multivariate technique, was utilized to separate groups based on the measured k variables in each sample, finding one or more linear combinations of the selected variables . The ade4 package was used to perform the analysis within the R environment …”

Section: Methodsmentioning

confidence: 99%

“…Discriminant analysis, a multivariate technique, was utilized to separate groups based on the measured k variables in each sample, finding one or more linear combinations of the selected variables. 40 The ade4 package was used to perform the analysis within the R environment. 41,42 Considering that most of the spectral sensors developed for agricultural purposes (e.g.…”

Section: Data Analysesmentioning

confidence: 99%

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Pre‐planting weed detection based on ground field spectral data

Pott

Amado

Schwalbert

et al. 2019

Pest Management Science

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BACKGROUND Site‐specific weed management (SSWM) demands higher resolution data for mapping weeds in fields, but the success of this tool relies on the efficiency of optical sensors to discriminate weeds relative to other targets (soils and residues) before cash crop establishment. The objectives of this study were to (i) evaluate the accuracy of spectral bands to differentiate weeds (target) and other non‐targets, (ii) access vegetation indices (VIs) to assist in the discrimination process, and (iii) evaluate the accuracy of the thresholds to distinguish weeds relative to non‐targets for each VI using training and validation data sets. RESULTS The main outcomes of this study for effectively distinguishing weeds from other non‐targets are (i) training and validation data exhibited similar spectral curves, (ii) red and near‐infrared spectral bands presented greater accuracy relative to the other bands, and (iii) the tested VIs increased the discrimination accuracy related to single bands, with an overall accuracy above 95% and a kappa above 0.93. CONCLUSION This study provided a novel approach to distinguish weeds from other non‐targets utilizing a ground‐level sensor before cash crop planting based on field spectral data. However, the limitations of this study are related to the spatial resolution to distinguish weeds that might be closer to the one this study presented, and also related to the soil and crop residues conditions at the time of collecting the readings. Overall the results presented contribute to an improved understanding of spectral signatures from different targets (weeds, soils, and residues) before planting time supporting SSWM. © 2019 Society of Chemical Industry

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Section: Methodsmentioning

confidence: 99%

Section: Data Analysesmentioning

confidence: 99%

Pre‐planting weed detection based on ground field spectral data

Pott

Amado

Schwalbert

et al. 2019

Pest Management Science

View full text Add to dashboard Cite

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“…The discriminant analysis, a multivariate technique, produces discriminant function based on their linear combinations of the predictors that can distinguish or separate the groups. Therefore, by discriminant analysis, it is possible to find out the potential influence of each variable in separating the group variable under study [ 23 ]. The purpose of using discriminant analysis in this study was to assess whether enabling factors have more discriminatory properties on the MSH package utilization than other elements of the healthcare function of the HBM model.…”

Section: Methodsmentioning

confidence: 99%

Adopting Andersen’s behavior model to identify factors influencing maternal healthcare service utilization in Bangladesh

Kabir

2021

PLoS ONE

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Background Equitable maternal healthcare service access and it’s optimum utilization remains a challenge for many developing countries like Bangladesh, and different predisposing, enabling, and need-based factors affect the level of maternal healthcare use. The evidently poor maternal healthcare service utilization and disparities among groups in Bangladesh are concerning considering its effect on maternal health outcomes. The study aimed to identify the factors that influence maternal healthcare service (MHS) utilization in Bangladesh by adopting Andersen’s behavior model of health service use as the theoretical framework. Methods The 2017–18 Bangladesh Demographic Health Survey (2017–18 BDHS) data were used which is nationally representative. The survey study used two-stage stratified sampling to select study households, and data were collected through face-to-face interviews. The desirable, moderate, and undesirable maternal health service (MHS) package was developed based on antenatal, and delivery care services use during pregnancy and childbirth. Multinomial logistic regression and discriminant analysis were performed to analyze the factors that affect MHS use. Results Out of 5,011 ever-married women, only 31.2% of women utilized the desirable level of MHS. The likelihood of using the desirable level of MHS package, relative to the undesirable category, was 9.38 times (OR: 9.38, 95% CI: 4.30–20.44) higher for women with a higher level of education compared to illiterate women, and the same trend was noticed for husband’s education. The wealth index had the highest standardized function coefficients (Beta coefficient: 0.49) in discriminatory function. Women with the richest wealth index were more than 23 times (OR: 23.27, 95% CI: 12.69–42.68) likely to have utilized desirable MHS than their poorest counterparts. The likelihood of service uses also varied according to the child’s birth order, administrative regions, and area of residence (rural vs. urban). Conclusions Policies and interventions directed towards poverty reduction, universal education, and diminishing geographical disparities of healthcare access might influence the desirable use of maternal healthcare services in Bangladesh.

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“…The The aim is to identify the contribution of each method in effectively distinguishing the groups concerning the OFA reference technique. 21 Significance for these tests was defined as P < .05. Following this, Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value were computed for the diagnostic evaluation of DI and NA, employing OFA as the reference.…”

Section: Statisticsmentioning

confidence: 99%

Comparison of the distraction index and Norberg angle with radiographic grading of canine hip dysplasia

Carneiro,

da Cruz,

Lima

et al. 2024

Vet Radiology Ultrasound

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The Orthopedic Foundation for Animals (OFA) radiographic grading system stands as a well‐established benchmark for categorizing hip dysplasia in canines. Although more objective techniques to quantify early hip laxity in young dogs, such as the Norberg angle (NA) and distraction index (DI), have been documented, there is a scarcity of published studies that directly compare these radiographic measures. The primary objectives of this prospective, analytical study were to assess and compare the NA and DI measures with OFA grades within a cohort of dogs. Thirty dogs (57 hip joints) were evaluated, with a mean age of 5.4 ± 2.9 years and a mean body weight of 34.3 ± 7.1 kg. The discriminative power of hip dysplasia for DI and NA used OFA as a reference were compared by multivariate discriminant analysis test. Using the DI (≤0.3) 12 joints were classified as normal, using NA (≥105°) 24 joints and using OFA (≤3) 29. When comparing the discriminant power of NA with OFA resulting similar (P = .8324) with correct classifications of 81% using cross validation, however, the discriminant power of dysplasia of the DI resulted significantly greater (P = .0034) than OFA with correct classifications of only 59% using cross‐validation, consequently it was possible determined that of 29 patients with OFA ≤ 3, 20 had DI > 0.3. These findings demonstrated that phenotypic healthy dogs according to OFA grading can present passive hip joint laxity, as demonstrated by radiographic evaluation with distraction. Furthermore, DI can contribute to the screening of CHD when evaluated in conjunction with OFA grading.

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Discriminant Analysis and Classification

Cited by 12 publications

References 1 publication

Pre‐planting weed detection based on ground field spectral data

Pre‐planting weed detection based on ground field spectral data

Adopting Andersen’s behavior model to identify factors influencing maternal healthcare service utilization in Bangladesh

Comparison of the distraction index and Norberg angle with radiographic grading of canine hip dysplasia

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