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Showing 1 - 20 results of 27 for search 'sample selection value before (feature OR features)*', query time: 0.18s Refine Results
  1. 1

    NEW ORGANIZATION PROCESS OF FEATURE SELECTION BY FILTER WITH CORRELATION-BASED FEATURES SELECTION METHOD by Olga Solovei

    Published 2022-09-01
    “… The subject of the article is feature selection techniques that are used on data preprocessing step before building machine learning models. …”
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  2. 2

    Impact wear behavior of austenitic steel bucket teeth based on machine learning by Zhihui Cai, Jianfeng Yan, Yandong Qiao, Rongjie Li, Yanchun Shi, Junping Zhang, Zhixiong Zhang

    Published 2025-05-01
    “…A particle swarm optimization support vector machine was employed to accurately predict wear depth. The mean values of the determination coefficient (R2) before and after feature selection were 0.96294 and 0.98074, respectively, further validating the accuracy of the feature selection process and providing a ranking of importance for identifying key factors to enhance wear resistance.…”
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  3. 3

    Ensemble learning approach for prediction of early complications after radiotherapy for head and neck cancer using CT and MRI radiomic features by Benyamin Khajetash, Seied Rabi Mahdavi, Alireza Nikoofar, Lee Johnson, Meysam Tavakoli

    Published 2025-04-01
    “…Combined $$T_1$$ weighted image-based models RT-BN, RT-LSVM-BN and RT-NN-LSVM-BN also show good performance having AUC values 0.97, 0.92, and 0.90, respectively. These results show that radiomic features from MR images obtained before radiotherapy can be used in addition to other metrics as personalized and unique biomarkers for prediction of early-onset xerostomia. …”
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    Selective Separation of Scandium in Acidic Water Using Carboxyl Functionalized Covalent Phosphonitrile Polymers by Yu BAI, Ayinuer WUSHUER, Lei OUYANG, Lijin HUANG, Qin SHUAI

    Published 2023-10-01
    “…Both materials have the ability to selectively adsorb Sc(III), with Kd values of 5.1×102mL/g and 4.0×103mL/g for Sc(III), respectively. …”
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  6. 6

    An Evaluation of the Possibility of Using Buckwheat Hulls as an Addition to Bread by Joanna Maria Klepacka, Marta Czarnowska-Kujawska

    Published 2024-02-01
    “…The test material consisted of a control bread (without the addition of husk), bread with 10 and 20% husk (mixed with flour at the stage of dough preparation), and bread with a surface sprinkled with buckwheat husk (25 g) before baking. The semi-consumer evaluation involved 33 pre-trained persons who determined the degree of acceptance (desirability) of the selected bread’s sensory characteristics (colour, texture, smell and taste) using the nine-point hedonic scale. …”
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  7. 7

    Investigating the Effects of Spectroscopic Method in Estimating Soluble Solid Content Values and Firmness of Cherries from an Environmental Point of View: Prediction of Environment... by Shirzad Naim, Shahgholi Gholamhossein, Ardabili Sina, Szymanek Mariusz

    Published 2025-03-01
    “…Next, by combining the feature selection method (relief) and the spectrometry method (vis-NIR), the effective wavelengths were extracted to estimate the soluble solid content (SSC) values and firmness of the cherry product. …”
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  8. 8

    Chemical Composition and Sensory Profile of Sauerkraut from Different Cabbage Hybrids by Elena V. Yanchenko, Galina S. Volkova, Elena V. Kuksova, Ivan I. Virchenko, Aleksey V. Yanchenko, Elena M. Serba, Maria I. Ivanova

    Published 2023-03-01
    “…The present research objective was to test several cabbage hybrids for natural fermentation, microbiological parameters, and native sugar content after four months of storage. The study featured twelve new-generation white cabbage hybrids of Russian selection and sauerkraut foods. …”
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  9. 9

    A donor heart scoring model to predict transplant outcomes by E. A. Tenchurina, M. G. Minina

    Published 2021-01-01
    “…In binomial logistic regression, non-selection of heart donor was used as a dependent variable, while donor characteristics were used as factor features. …”
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  10. 10

    Identification of exosome-related genes in NSCLC via integrated bioinformatics and machine learning analysis by Zhenjie Sun, Tianyu Du, Guosheng Yang, Yinghuan Sun, Xuyang Xiao

    Published 2025-07-01
    “…However, further experimental verification is required to assess its practical value for NSCLC and other lung cancer subtypes before clinical application.…”
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  11. 11

    Prediction of KRAS gene mutations in colorectal cancer using a CT-based radiomic model by Wenjing Wang, Qingbiao Zhang, Shimei Fan, Yuyin Wang, Xingyan Le, Min Ai, Chunqi Du, Junbang Feng, Chuanming Li

    Published 2025-05-01
    “…The Delong test was employed to assess the differences between the various models.ResultsAfter feature selection, the top 8 features with the highest mutual information scores were extracted to construct a prediction model. …”
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  12. 12

    Ensemble Machine Learning for the Prediction and Understanding of the Refractive Index in Chalcogenide Glasses by Miruna-Ioana Belciu, Alin Velea

    Published 2025-04-01
    “…This study employs various machine learning models to reliably predict the refractive index at 20 °C using a small dataset of 541 samples extracted from the SciGlass database. The input for the algorithms consists of a selected set of physico-chemical features computed for the chemical composition of each entry. …”
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  13. 13

    Révision de l’espèce Homo erectus (Dubois, 1893) by Valéry Zeitoun

    Published 2000-06-01
    “…Those arguments have revealed that the index formulation in logarithmic form usually allows to use them without any problem in the sight of the Laplace-Gauss law. So for a given feature, if the normality is not respected in the reference set then it is not taken into account.An analysis is realized to select the discriminant index, those allowing the grouping or the splitting of different individuals. …”
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  14. 14

    Evaluation of landslide susceptibility in Nujiang Prefecture based on optimized MaxEnt model by LI Yimin, XIANG Qianying, DENG Xuanlun, FENG Xianjie

    Published 2025-01-01
    “…The MaxEnt model feature combination (FC) and regularization multi⁃plier (RM) parameters were optimized, and the sample of the akaike information criterion(AICc), Omission Rate (OR) and AUC (Area Under Curve) value before optimization were compared with that after opitimazation,and the occurrence of landslide hazards based on the optimized MaxEnt model was predictedto realize the landslide susceptibility evaluation in Nujiang Prefecture.ResultsThe optimized MaxEnt model has excellent applicability in predicting landslide susceptibility in the study area (AUC=0.913)). …”
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  15. 15

    Characterization of the attributes impacting industrial adoption of tree tomato fruit varieties in Kenya by Isaac M. Maitha, Michael W. Okoth, Lucy G. Njue, Duncan O. Mbuge

    Published 2025-12-01
    “…Subjective color assessment was used to sort the fruits before randomly selecting samples for physicochemical characterization. …”
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  16. 16

    Plasma Acylcarnitines and Amino Acid Levels As an Early Complex Biomarker of Propensity to High-Fat Diet-Induced Obesity in Mice. by Olga Horakova, Jana Hansikova, Kristina Bardova, Alzbeta Gardlo, Martina Rombaldova, Ondrej Kuda, Martin Rossmeisl, Jan Kopecky

    Published 2016-01-01
    “…Taking advantage of a high phenotypic variation in diet-induced obesity in C57BL/6J mice, 12-week-old male and female mice (n = 155) were fed a high-fat diet (lipids ~32 wt%) for a period of 10 weeks, while body weight gain (BWG) and changes in insulin sensitivity (ΔHOMA-IR) were assessed. Plasma samples were collected before (week 4) and after (week 22) high-fat feeding. …”
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  17. 17

    Evaluation of the River Salinity Changes using Hydrochemical Method in Arid Area (Case Study: Namaklan River, Ilam) by Maryam Mousavi, Noredin Rostami, Haji Karimi

    Published 2018-05-01
    “…The points were selected in areas where the flow of water was stable and without turbulence which can mix sediment to the water sample and at each point, the water samples collected by 1-liter bottles. …”
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    Liver diseases at new coronavirus infection in pregnant women of Samara region by M. A. Kachkovskii, O. V. Kosheleva, G. M. Mingulova

    Published 2021-10-01
    “…A retrospective analysis of medical records of 43 pregnant women aged 19 to 39 years (mean age 29.1 ± 5.4 years) who were hospitalized with laboratory-confirmed COVID-19 infection was performed. The selection was carried out by the method of continuous sampling.Results. 17 women (39.5%) had an acute respiratory viral disease, 26 people (60.5%) were diagnosed with bilateral polysegmental pneumonia with pulmonary tissue damage from 5 to 25%. …”
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  20. 20

    Treatment of uterine fibroid: focus on endometrial receptivity. A pilot randomized prospective study by Yulia E. Dobrokhotova, Irina A. Lapina, Valeriia M. Gomzikova, Yury А. Sorokin, Eleonora T. Khatagova, Ayshan R. Allakhverdieva, Mariya A. Olkhovskaya

    Published 2024-12-01
    “…The samples from all patients were subjected to immunohistochemical examination before the start of drug therapy and at the first menstruation after the end of treatment. …”
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