An Attribute-Weighted Bayes Classifier Based on Asymmetric Correlation Coefficient

2020 ◽  
Vol 34 (10) ◽  
pp. 2050025
Author(s):  
Jingxian Liu ◽  
Yulin Zhang
Keyword(s):  
Correlation Coefficient ◽  
Binary Classification ◽  
Correlation Coefficients ◽  
Estimation Algorithm ◽  
Classification Performance ◽  
Bayes Estimation ◽  
Bayes Classifier ◽  
Multiple Classification ◽  
Category Labels ◽  
Asymmetric Correlation

In this research, an attribute-weighted one-dependence Bayes estimation algorithm based on the asymmetric correlation coefficient is proposed. The asymmetric correlation coefficients Tau_y and Lambda_y, respectively, are used to calculate the correlation between parent attributes and category labels, then the result of calculation is regarded as weight to the parent attribute. The algorithm is applied to eight types of different datasets including binary classification and multiple classification from the UCI database. By comparing the time complexity and classification accuracy, experimental results show that the algorithm can significantly improve the classification performance with less prediction error. In addition, several baseline methods such as KNN, ANN, logistic regression and SVM are used for comparison with the proposed method.

IMPROVEMENT OF SPRING DURUM WHEAT SELECTION METHODOLOGIES UNDER CLIMATE CHANGE CONDITIONS

1970 ◽  
pp. 33-36
Author(s):  
А. I. Grabovets ◽  
V. P. Kadushkina ◽  
S. А. Kovalenko
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Correlation Coefficient ◽  
Harvest Index ◽  
Unit Area ◽  
Correlation Coefficients ◽  
Chemical Mutagenesis ◽  
Main Method ◽  
The Relationship ◽  
Selection Of

With the growing aridity of the climate on the Don, it became necessary to improve the methodology for conducting the  breeding of spring durum wheat. The main method of obtaining the source material remains intraspecific step hybridization. Crossings were performed between genetically distant forms, differing in origin and required traits and properties. The use of chemical mutagenesis was a productive way to change the heredity of genotypes in terms of drought tolerance. When breeding for productivity, both in dry years of research and in favorable years, the most objective markers were identified — the size of the aerial mass, the mass of grain per plant, spike, and harvest index. The magnitude of the correlation coefficients between the yield per unit area and the elements of its structure is established. It was most closely associated with them in dry years, while in wet years it decreased. Power the correlation of the characteristics of the pair - the grain yield per square meter - the aboveground biomass averaged r = 0.73, and in dry years it was higher (0.91) than in favorable ones (0.61 - 0.70) , between the harvest and the harvest index - r = 0.81 (on average). In dry years, the correlation coefficient increased to 0.92. Research data confirms the greatest importance of the mass of grain from one ear and the plant in the formation of grain yield per unit area in both dry and wet years. In dry years, the correlation coefficient between yield and grain mass per plant was on average r = 0.80; in favorable years, r = 0.69. The relationship between yield and grain mass from the ear was greater — r = 0.84 and r = 0.82, respectively. Consequently, the breeding significance of the aboveground mass and the productivity of the ear, as a criterion for the selection of the crop, especially increases in the dry years. They were basic in the selection.

scholarly journals Development and Relative Validity of a Semiquantitative Food Frequency Questionnaire to Estimate Dietary Intake among a Multi-Ethnic Population in the Malaysian Cohort Project

Nutrients ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 1163
Author(s):  
Suzana Shahar ◽  
Mohd Razif Shahril ◽  
Noraidatulakma Abdullah ◽  
Boekhtiar Borhanuddin ◽  
Mohd Arman Kamaruddin ◽  
...  
Keyword(s):  
Vitamin C ◽  
Correlation Coefficient ◽  
Food Frequency Questionnaire ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Weighted Kappa ◽  
Dietary Intakes ◽  
Food Frequency ◽  
Relative Validity ◽  
Spearman’S Correlation

Measuring dietary intakes in a multi-ethnic and multicultural setting, such as Malaysia, remains a challenge due to its diversity. This study aims to develop and evaluate the relative validity of an interviewer-administered food frequency questionnaire (FFQ) in assessing the habitual dietary exposure of The Malaysian Cohort (TMC) participants. We developed a nutrient database (with 203 items) based on various food consumption tables, and 803 participants were involved in this study. The output of the FFQ was then validated against three-day 24-h dietary recalls (n = 64). We assessed the relative validity and its agreement using various methods, such as Spearman’s correlation, weighed Kappa, intraclass correlation coefficient (ICC), and Bland–Altman analysis. Spearman’s correlation coefficient ranged from 0.24 (vitamin C) to 0.46 (carbohydrate), and almost all nutrients had correlation coefficients above 0.3, except for vitamin C and sodium. Intraclass correlation coefficients ranged from −0.01 (calcium) to 0.59 (carbohydrates), and weighted Kappa exceeded 0.4 for 50% of nutrients. In short, TMC’s FFQ appears to have good relative validity for the assessment of nutrient intake among its participants, as compared to the three-day 24-h dietary recalls. However, estimates for iron, vitamin A, and vitamin C should be interpreted with caution.

Comparison of visual (MUNSELL) and instrumental measures (CIELAB) of coloured textile standard samples

2019 ◽  
Vol 23 (4) ◽  
pp. 340-354
Author(s):  
Asim Kumar Roy Choudhury ◽  
Biswajit Naskar
Keyword(s):  
Correlation Coefficient ◽  
Design Methodology ◽  
Correlation Coefficients ◽  
Standard Samples ◽  
Content Type ◽  
Psychophysical Data ◽  
Physical Data ◽  
Hue Angle ◽  
Munsell Scale

Purpose This paper aims to compare visual (Munsell) and instrumental (CIELAB) attributes of SCOTDIC colour standards. Design/methodology/approach SCOTDIC cotton and polyester standards of defined hue, value and chroma were subjected to spectrophotometric assessment for finding the corresponding instrumental parameters. The visual and instrumental parameters were compared. Findings The correlation between SCOTDIC value and CIELAB lightness is quite high. Correlation coefficient between SCOTDIC hue and CIELAB hue angle and the correlation between SCOTDIC chroma and CIELAB chroma were only moderate because the CIELAB chroma varied widely at higher chroma. When the standards of SCOTDIC hues having erratic hue angles at two extremes are excluded, the Correlation coefficients between SCOTDIC hue and CIELAB hue angle become high. Research limitations/implications The psychophysical data (visual) are difficult to match with physical data (instrumental). Originality/value The object of the present research is to study and compare visual (Munsell) and instrumental (CIELAB) colorimetric parameters. Munsell scale is physically exemplified by SCOTDIC fabric samples available in two sets, namely, cotton and polyester sets.

Effect of Surface Roughness on Slip Resistance of Rubber

2011 ◽  
Vol 189-193 ◽  
pp. 1538-1542
Author(s):  
Li Xiao Jia ◽  
Yong Zhen Zhang ◽  
Yong Ping Niu ◽  
San Ming Du ◽  
Jian Li
Keyword(s):  
Surface Roughness ◽  
Correlation Coefficient ◽  
Correlation Coefficients ◽  
Roughness Parameters ◽  
Test Conditions ◽  
Slip Resistance ◽  
Materials Used ◽  
Almost All ◽  
Effect Of Surface

In order to decrease accidents of slips and falls, COFs of rubber samples with different surface roughness were measured by Brungraber Mark II. And the correlation coefficients between roughness parameters and COF were calculated. The rusults have shown that the COF increases with surface roughness and the correlation coefficient between Sq and COF is highest. In general, almost all the roughness parameters used in the study have high correlation with COF. Parameters had the highest correlation with COF depends on the materials used and test conditions.

scholarly journals Innovative Correlation Coefficient Measurement with Fuzzy Data

2016 ◽  
Vol 2016 ◽  
pp. 1-11
Author(s):  
Berlin Wu ◽  
Chin Feng Hung
Keyword(s):  
Mathematics Achievement ◽  
Correlation Coefficient ◽  
Empirical Studies ◽  
Correlation Coefficients ◽  
Interval Data ◽  
Fuzzy Data ◽  
Pearson’S Correlation Coefficient ◽  
Coefficient Measurement ◽  
The Relationship ◽  
Fuzzy Interval

Correlation coefficients are commonly found with crisp data. In this paper, we use Pearson’s correlation coefficient and propose a method for evaluating correlation coefficients for fuzzy interval data. Our empirical studies involve the relationship between mathematics achievement and other projects.

scholarly journals Multiple Naïve Bayes Classifiers Ensemble for Traffic Incident Detection

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Qingchao Liu ◽  
Jian Lu ◽  
Shuyan Chen ◽  
Kangjia Zhao
Keyword(s):  
Decision Tree ◽  
Naive Bayes ◽  
Classification Performance ◽  
Naïve Bayes ◽  
Classifier Ensemble ◽  
Optimal Threshold ◽  
Incident Detection ◽  
Bayes Classifier ◽  
Traffic Incident ◽  
Better Than

This study presents the applicability of the Naïve Bayes classifier ensemble for traffic incident detection. The standard Naive Bayes (NB) has been applied to traffic incident detection and has achieved good results. However, the detection result of the practically implemented NB depends on the choice of the optimal threshold, which is determined mathematically by using Bayesian concepts in the incident-detection process. To avoid the burden of choosing the optimal threshold and tuning the parameters and, furthermore, to improve the limited classification performance of the NB and to enhance the detection performance, we propose an NB classifier ensemble for incident detection. In addition, we also propose to combine the Naïve Bayes and decision tree (NBTree) to detect incidents. In this paper, we discuss extensive experiments that were performed to evaluate the performances of three algorithms: standard NB, NB ensemble, and NBTree. The experimental results indicate that the performances of five rules of the NB classifier ensemble are significantly better than those of standard NB and slightly better than those of NBTree in terms of some indicators. More importantly, the performances of the NB classifier ensemble are very stable.

scholarly journals Psychometric Properties of the MyotonPRO in Dementia Patients with Paratonia

Gerontology ◽  
2017 ◽  
Vol 64 (4) ◽  
pp. 401-412 ◽  
Author(s):  
Hans Drenth ◽  
Sytse U. Zuidema ◽  
Wim P. Krijnen ◽  
Ivan Bautmans ◽  
Cees van der Schans ◽  
...  
Keyword(s):  
Psychometric Properties ◽  
Correlation Coefficient ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Functional Mobility ◽  
Future Research ◽  
Minimal Detectable Change ◽  
Muscle Properties ◽  
Dementia Patients ◽  
Longitudinal Outcome

Background: Paratonia is a distinctive form of hypertonia, causing loss of functional mobility in early stages of dementia to severe high muscle tone and pain in the late stages. For assessing and evaluating therapeutic interventions, objective instruments are required. Objective: Determine the psychometric properties of the MyotonPRO, a portable device that objectively measures muscle properties, in dementia patients with paratonia. Methods: Muscle properties were assessed with the MyotonPRO by 2 assessors within one session and repeated by the main researcher after 30 min and again after 6 months. Receiver operating characteristic curves were constructed for all MyotonPRO outcomes to discriminate between participants with (n = 70) and without paratonia (n = 82). In the participants with paratonia, correlation coefficients were established between the MyotonPRO outcomes and the Modified Ashworth Scale for paratonia (MAS-P) and muscle palpation. In participants with paratonia, reliability (intraclass correlation coefficient) and agreement values (standard error of measurement and minimal detectable change) were established. Longitudinal outcome from participants with paratonia throughout the study (n = 48) was used to establish the sensitivity for change (correlation coefficient) and responsiveness (minimal clinical important difference). Results: Included were 152 participants with dementia (mean [standard deviation] age of 83.5 [98.2]). The area under the curve ranged from 0.60 to 0.67 indicating the MyotonPRO is able to differentiate between participants with and without paratonia. The MyotonPRO explained 10-18% of the MAS-P score and 8-14% of the palpation score. Interclass correlation coefficients for interrater reliability ranged from 0.57 to 0.75 and from 0.54 to 0.71 for intrarater. The best agreement values were found for tone, elasticity, and stiffness. The change between baseline and 6 months in the MyotonPRO outcomes explained 8-13% of the change in the MAS-P scores. The minimal clinically important difference values were all smaller than the measurement error. Conclusion: The MyotonPRO is potentially applicable for cross-sectional studies between groups of paratonia patients and appears less suitable to measure intraindividual changes in paratonia. Because of the inherent variability in movement resistance in paratonia, the outcomes from the MyotonPRO should be interpreted with care; therefore, future research should focus on additional guidelines to increase the clinical interpretation and improving reproducibility.

scholarly journals AB0798 IS THERE A REPRODUCIBILITY OF THE HISTOGRAM AND GRAY SCALE IN ECOEXTRUCTURAL DAMAGES IN RHEUMATOTOLOGICAL DISEASES?

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1423.2-1424
Author(s):  
J. A. Mendonça ◽  
I. Siste de Almeida Aoki ◽  
C. C. Cavuto ◽  
V. A. Leandro-Merhi ◽  
J. L. B. D. Aquino
Keyword(s):  
Correlation Coefficient ◽  
Intraclass Correlation Coefficient ◽  
Rheumatic Diseases ◽  
Femoral Condyle ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Concordance Correlation Coefficient ◽  
Image Method ◽  
Concordance Correlation ◽  
Gray Scale

Background:The gray scale (GS) in high resolution ultrasound is already well validated for use in rheumatological diseases, but the color map or the histogram, can be considered a new proposal, to better define and complement the echotextural damages detection1.Objectives:To calculate the lesions area measures reproducibility index in arthropathies, between 3 blind evaluators and correlate these measures using the GS and the histogram.Methods:Observational and retrospective study approved by the ethics committee of the Pontifical Catholic University of Campinas, with the opinion number: 1.526.307. A total of 29 patients have been assessed (31% males and 69% females) on period 2014 to 2019 in Rheumatology service. A MyLab 50 -Esaote equipment was used with frequency transducer that ranged between 6.0 and 18.0 MHz, 10 different area measures were performed from each recorded images previously, by the GS and the histogram. Statistical analysis: Spearman’s correlation coefficients, Lin’s concordance coefficient (CCC) and the intraclass correlation coefficient (ICC) and their respective 95% confidence intervals, with the SPSS software package for Windows v. 17.0 (SPSS Inc., Chicago, IL, USA).Results:Average age 43.5 ± 21.5 years of age; with disease duration that varied between ≤ 1 month (48.3%) and ≥36 months (24.1%); with the following diseases: juvenile idiopathic arthritis (17.24%); osteoarthritis (13.79%); psoriatic arthritis (13.79%); undifferentiated spondyloarthritis (3.44%); gout (20.68%); rheumatoid arthritis (27.58%) and reactive arthritis (3.44%). A total of 840 measures of exudative (27.58%), proliferative (27.58%) and snowstorm appearance (6.89%) synovitis were performed; femoral-condyle cartilage (3.44%); synovial cyst (3.44%); paratendinitis (6.89%); calcification (3.44%); nail enthesitis (3.44%); tenosynovitis (6.89%) and tophi (10.34%) (Figure 1). The concordance correlation coefficient showed values closer to 1; p <0.001, the intraclass correlation coefficients with excellent reproducibility (ICC ≥ 0.75); p <0.001, always in relation to the three evaluators (Table 1) and the Spearman correlation between the GS and the histogram ranged from rs = 0.665 to rs = 1,000; p <0.001.Conclusion:The histogram can be considered an image method to better identify echotextural damages.References:[1]Mendonça J, Provenza J, Guissa V, et al AB1059 2D Histogram Ultrasound and 3D Ultrasound Correlation in Rheumatic Diseases Annals of the Rheumatic Diseases 2015; 74:1253-1254.Table 1.Concordance Correlation Coefficient (CCC) and Intraclass Correlation Coefficient (ICC):EvaluatorsGS - CCC(IC 95%)p-valorHistogram (IC 95%)p-valor1 e 20,998(0,994-0,999)<0,0010,999(0,995-1,000)<0,0011 e 30,998(0,995-0,999)<0,0010,999(0,995-1,000)<0,0012 e 30,992(0,980-0,997)<0,010,996(0,979-0,999)<0,01Standard by US 2DICCp-valorGS0,997(0,992-0,999)<0,001Histogram0,998(0,992-0,999)<0,001Legends: Gray Scale (GS).Figure 1.Patient with gout: A and B: Tophi area measures (star) in right metatarsos and efusion (arrow) by GS (45 mm2) and histogram (39 mm2), respectively.Disclosure of Interests:José Alexandre Mendonça Speakers bureau: Novartis, Janssen, Bristol, UCB, Isabella Siste de Almeida Aoki: None declared, Caique Chagas Cavuto: None declared, Vânia Aparecida Leandro-Merhi: None declared, José Luis Braga de Aquino: None declared

scholarly journals Phybrata Sensors and Machine Learning for Enhanced Neurophysiological Diagnosis and Treatment

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7417
Author(s):  
Alex J. Hope ◽  
Utkarsh Vashisth ◽  
Matthew J. Parker ◽  
Andreas B. Ralston ◽  
Joshua M. Roper ◽  
...  
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Random Forest ◽  
Binary Classification ◽  
Classification Performance ◽  
Support Vector ◽  
Use Case ◽  
Signal Features ◽  
Test Population

Concussion injuries remain a significant public health challenge. A significant unmet clinical need remains for tools that allow related physiological impairments and longer-term health risks to be identified earlier, better quantified, and more easily monitored over time. We address this challenge by combining a head-mounted wearable inertial motion unit (IMU)-based physiological vibration acceleration (“phybrata”) sensor and several candidate machine learning (ML) models. The performance of this solution is assessed for both binary classification of concussion patients and multiclass predictions of specific concussion-related neurophysiological impairments. Results are compared with previously reported approaches to ML-based concussion diagnostics. Using phybrata data from a previously reported concussion study population, four different machine learning models (Support Vector Machine, Random Forest Classifier, Extreme Gradient Boost, and Convolutional Neural Network) are first investigated for binary classification of the test population as healthy vs. concussion (Use Case 1). Results are compared for two different data preprocessing pipelines, Time-Series Averaging (TSA) and Non-Time-Series Feature Extraction (NTS). Next, the three best-performing NTS models are compared in terms of their multiclass prediction performance for specific concussion-related impairments: vestibular, neurological, both (Use Case 2). For Use Case 1, the NTS model approach outperformed the TSA approach, with the two best algorithms achieving an F1 score of 0.94. For Use Case 2, the NTS Random Forest model achieved the best performance in the testing set, with an F1 score of 0.90, and identified a wider range of relevant phybrata signal features that contributed to impairment classification compared with manual feature inspection and statistical data analysis. The overall classification performance achieved in the present work exceeds previously reported approaches to ML-based concussion diagnostics using other data sources and ML models. This study also demonstrates the first combination of a wearable IMU-based sensor and ML model that enables both binary classification of concussion patients and multiclass predictions of specific concussion-related neurophysiological impairments.

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