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ANOVA - Crossref

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Last Updated: 10 June 2022

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Optimization of the ANOVA Procedure for Support Vector Machines

"This paper discusses how a feature selection strategy based on variance analysis can be optimized for Support Vector Machines to increase execution time and accuracy. " To ensure the success of the support vector classifier, we've introduced new SVMs prior to running the ANOVA. We recommend a variety of ANOVA-SVM experiments that are simple to use, but also raise the SVM's accuracy and computation time in comparison to existing methods such as the Mixed Integer Linear Feature Selection method. ".

Source link: https://doi.org/10.35940/ijrte.d7375.118419


USING OF RM-ANOVA IN R AND SPSS SOFTWARE ON THE EXAMPLE OF PROSPECTIVE ANALYSIS OF GLUCOSE TOLERANCE TEST RESULTS IN PATIENTS WITH POLYCYSTIC OVARY SYNDROME

"For better understanding of the technique, we present a concrete example based on the results obtained blood glucose levels in patients with PCOS and healthy women from various ethnic groups after an oral glucose tolerance test. " In addition, syntax and graphs are included in the R and SPSS applications for RM-ANOVA.

Source link: https://doi.org/10.33396/1728-0869-2019-3-53-61


Equivalence between Sobolev spaces of first-order dominating mixed smoothness and unanchored ANOVA spaces on ℝ^{𝕕}

"We show that a modified of the classical Sobolev space of first-order dominating mixed smoothness is equivalent to the unanchored ANOVA space on R d mathbb R d. d t geq 1 d ggeq 1 d d. Initially launched by Nichols and Kuo in 2014 to investigate the approximations of integrals on unbounded domains; whereas a series of papers by Griebel, Kuo, and Sloan focusing on integration's smoothing effect in an attempt to establish a robust explanation of why QMC methods work so well for certain non-smooth integrands with kinks or jumps coming from option price rises were launched by Nichols and Kuo.

Source link: https://doi.org/10.1090/mcom/3718


Comparative investigations of cryo-treated and untreated inserts on machinability of AISI 1050 by using response surface methodology, ANOVA and Taguchi design

Using Taguchi mixed design and Response Surface Methodology, the aim is to investigate the machinability of the AISI 1050 workpieces with cutting inserts, treated under extreme cryogenic heat, and untreated ones, as well as determining the optimal cutting parameters and cutting force for surface roughness and cutting force. " The machining experiment was carried out on a CNC lathe with machining parameters such as three feed rates, three cutting speeds, and a constant depth of cut under dry conditions and with heat treatment. Taguchi design L18 is based on three main features; cutting parameters with each one of three levels; and heat treatment condition with two levels; as is known, Taguchi design L18 consists of three factors; as is known, Taguchi design L18 consists of three factors; cutting parameters with each one of three levels; and a heat treatment condition with two levels. In addition, ANOVA findings and RSM reveal that feed rate was one of the most influential control factors on surface roughness and cutting force. RSM and Taguchi mixed design therefore predicts that experimental results will closely match prediction results with forecast results. ".

Source link: https://doi.org/10.1177/09544062211023117


Comparison of Multivariate ANOVA-Based Approaches for the Determination of Relevant Variables in Experimentally Designed Metabolomic Studies

"The use of chemometric methods based on variance analysis allows for the determination of the experimental factors used in a research's study's statistical significance. " However, classical multivariate ANOVA has a variety of aspects that make it impractical for dealing with metabolomics results, which makes it impractical for dealing with metabolomics results. However, key measures reported by GASCA appear to be more reliable, as there is a strong similarity with those variables found by the commonly used partial least squares discriminant analysis device. ".

Source link: https://doi.org/10.3390/molecules27103304


A novel framework based on deep learning and ANOVA feature selection method for diagnosis of COVID-19 cases from chest X-ray Images

"Abstract" was first detected in Wuhan and quickly sprang internationally, causing rioting on the economy and people's daily lives. To identify and care for patients in the early stages of COVID-19 and minimize the virus's transmission, a reliable detection system is required to identify and treat them. In fact, superior results are obtained relative to RT-PCR, chest CT scans, and chest X-ray images. X-ray photographs are most popular for screening due to the scarcity and high cost of CT scan services. This method achieved 98. 72% accuracy for two-class classification and 92% for three-class classification.

Source link: https://doi.org/10.1101/2021.10.10.21264809

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions