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classification toolbox for matlab  (MathWorks Inc)


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    MathWorks Inc classification toolbox for matlab
    Classification Toolbox For Matlab, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 455 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/classification+toolbox+for+matlab/Instrument+Control+Toolbox/pmc12878783-135-32-35
    Average 96 stars, based on 455 article reviews
    classification toolbox for matlab - by Bioz Stars, 2026-10
    96/100 stars

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    Article Title: 1H Nuclear Magnetic Resonance (NMR)-Based Metabolome Diversity of Seabuckthorn (H. rhamnoides L.) Berries Originating from Two Geographical Regions of Indian Himalayas
    Article Snippet: A comprehensive analysis of crucial metabolites in seabuckthorn (Hippophae rhamnoides L.) was conducted by analyzing the methanolic extract of berries originating from 37 geographical sites of the Indian Himalayas by using 1H NMR-based metabolome profiling.. The concentration of 103 metabolites was annotated, of which two, spermidine and beta-alanine, were reported for the first time in higher concentrations in berries collected from Himachal Pradesh and Jammu and Kashmir.. The quantified peak intensity matched with standard compounds present in the different databases, including Madison-Qingdao Metabolomics Consortium Database (MMCD), Human Metabolome Database (HMDB), and Spectral Database of Organic Compounds (SBDS).

    Article Title: Combined Biospectroscopy with Multivariate Analysis for the Differential Diagnosis of Leptospirosis Disease: A Pilot Study
    Article Snippet: All computational analyses, including importing, preprocessing, and constructing multivariate classification models, were performed within the MATLAB 2022 environment (MathWorks Inc., Natick, MA) using the PLS Toolbox version 9.2 (Eigenvector Research Inc.), the Classification Toolbox for MATLAB ( https://michem.unimib.it/download/matlab-toolboxes/classification-toolbox-for-matlab/ ), and custom laboratory-made routines.

    Article Title: Establishing spectrochemical changes in the natural history of oesophageal adenocarcinoma from tissue Raman mapping analysis
    Article Snippet: The data analysis was performed within MATLAB® R2014b (MathWorks, Inc., USA) using the Classification Toolbox for MATLAB [6], the HYPER-Tools toolbox for MATLAB [7], and in-house-developed algorithms.

    Article Title: Electronic nose technology for the detection of ergot alkaloid in soft wheat and identification of the relevant volatile compounds by solid phase microextraction/gas chromatography-high resolution Orbitrap-mass spectrometry coupled to chemometrics.
    Article Snippet: Partial least squares-discriminant analysis (PLS-DA) and SVM were then performed on the autoscaled data of the data sets using the classification toolbox for MATLAB (MATLAB software 2023a) (Ballabio & Consonni, 2013).

    Article Title: Experimental Data Based Machine Learning Classification Models with Predictive Ability to Select in Vitro Active Antiviral and Non-Toxic Essential Oils
    Article Snippet: MATLAB software, Version 9.1.0 (R2016b; The MathWorks, MA, USA), using PCA Toolbox for MATLAB (version 1.3; PCA, unsupervised data analysis) and Classification Toolbox for MATLAB (version 5.0; PLS-DA, supervised data analysis) [ , ] was used for all calculations.

    Article Title: Establishing spectrochemical changes in the natural history of oesophageal adenocarcinoma from tissue Raman mapping analysis
    Article Snippet: The data analysis was performed within MATLAB® R2014b (MathWorks, Inc., USA) using the Classification Toolbox for MATLAB [ ], the HYPER-Tools toolbox for MATLAB [ ], and in-house-developed algorithms.

    Software:

    Article Title: Developmental Dysregulation of Synaptic and Myelin-Related Genes in Frontal Cortex and Serum Infrared Spectroscopy Signature in the Valproic Acid Model of Autism
    Article Snippet: .. The spectral data processing was performed within MATLAB R2012b software (MathWorks Inc., USA) using the PLS Toolbox version 7.9.3 (Eigenvector Research Inc., USA) for pre-processing and the Classification Toolbox for MATLAB ( ) for classification. ..

    Article Title: Evaluation of adulteration in distillate samples of Rosa damascena Mill using colorimetric sensor arrays, chemometric tools and dispersive liquid-liquid microextraction-GC-MS.
    Article Snippet: Funding information Shiraz University of Medical Sciences, Grant/ Award Number: 20245 Abstract Introduction: Rosa damascena Mill distillate and its essential oil are widely used in cosmetics, perfumes and food industries.. Therefore, the methods of detection for its authentication is an important issue.. Objectives: We suggest colorimetric sensor array and chemometric methods to discriminate natural Rosa distillate from synthetic adulterates.



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