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  • Open Access


    Industrial Food Quality Analysis Using New k-Nearest-Neighbour methods

    Omar Fetitah1, Ibrahim M. Almanjahie2,3, Mohammed Kadi Attouch1,*, Salah Khardani4

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2681-2694, 2021, DOI:10.32604/cmc.2021.015469

    Abstract The problem of predicting continuous scalar outcomes from functional predictors has received high levels of interest in recent years in many fields, especially in the food industry. The k-nearest neighbor (k-NN) method of Near-Infrared Reflectance (NIR) analysis is practical, relatively easy to implement, and becoming one of the most popular methods for conducting food quality based on NIR data. The k-NN is often named k nearest neighbor classifier when it is used for classifying categorical variables, while it is called k-nearest neighbor regression when it is applied for predicting noncategorical variables. The objective of this paper is to use the… More >

  • Open Access


    The k Nearest Neighbors Estimator of the M-Regression in Functional Statistics

    Ahmed Bachir1, *, Ibrahim Mufrah Almanjahie1, 2, Mohammed Kadi Attouch3

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2049-2064, 2020, DOI:10.32604/cmc.2020.011491

    Abstract It is well known that the nonparametric estimation of the regression function is highly sensitive to the presence of even a small proportion of outliers in the data. To solve the problem of typical observations when the covariates of the nonparametric component are functional, the robust estimates for the regression parameter and regression operator are introduced. The main propose of the paper is to consider data-driven methods of selecting the number of neighbors in order to make the proposed processes fully automatic. We use the More >

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