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Wyszukujesz frazę "linear discriminant analysis" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
An identification source of variation on the water quality pattern in the Malacca River basin using chemometric approach
Autorzy:
Hua, A. K.
Powiązania:
https://bibliotekanauki.pl/articles/204612.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hierarchical cluster analysis
discriminant analysis
principal component analysis
multiple linear
regression analysis
Opis:
The Malacca River basin experienced river water pollution which caused a major deterioration to the ecosystems and environmental health. This study is carried out to assess the water quality data and identify the pattern of water pollution sources in the study area, and also to develop a predictive performance of water quality in the Malacca River basin. A chemometric approach using a combination of HCA, DA, PCA, and MLR, was applied into twenty water quality variables from nine sampling stations that were collected from January until December of 2015 in the river basin. HCA pointed out three clusters, namely Cluster 1 (C1) with low pollution source, Cluster 2 (C2) with moderate pollution source, and Cluster 3 (C3) with high pollution source. In the DA analysis, the results showed 21 variables, 12 variables, and 9 variables for standard mode, forward stepwise mode, and backward stepwise mode, respectively. Meanwhile, the PCA indicated that the main source of pollutants is detected from residential, industrial, commercial, agricultural, animal livestock, as well as forest land. Among the three models developed from MLR analysis, C3 with a high pollution source is detected to be the most suitable model to be used for the prediction of Water Quality Index in the Malacca River basin. This study proposed for an effective river water quality management by having new water quality monitoring network to be designed for more practical use in order to reduce time and effort, as well as cost saving purposes.
Źródło:
Archives of Environmental Protection; 2018, 44, 4; 111-122
2083-4772
2083-4810
Pojawia się w:
Archives of Environmental Protection
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On the binary classification problem in discriminant analysis using linear programming methods
Autorzy:
Olusola, Michael O.
Onyeagu, Sydney I.
Powiązania:
https://bibliotekanauki.pl/articles/406591.pdf
Data publikacji:
2020
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
binary classification
discriminant analysis
error rate
hit rate
linear programming
Opis:
This paper is centred on a binary classification problem in which it is desired to assign a new object with multivariate features to one of two distinct populations as based on historical sets of samples from two populations. A linear discriminant analysis framework has been proposed, called the minimised sum of deviations by proportion (MSDP) to model the binary classification problem. In the MSDP formulation, the sum of the proportion of exterior deviations is minimised subject to the group separation constraints, the normalisation constraint, the upper bound constraints on proportions of exterior deviations and the sign unrestriction vis-à-vis the non-negativity constraints. The two-phase method in linear programming is adopted as a solution technique to generate the discriminant function. The decision rule on group-membership prediction is constructed using the apparent error rate. The performance of the MSDP has been compared with some existing linear discriminant models using a previously published dataset on road casualties. The MSDP model was more promising and well suited for the imbalanced dataset on road casualties.
Źródło:
Operations Research and Decisions; 2020, 30, 1; 119-130
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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