Výsledky vyhledávání - "Fateme Moslehi"

Akademický článek

Effects of Pediococcus pentosaceus as a probiotic on intestinal microbiota and body composition of Siberian sturgeon, Acipenser baerii Brandt, 1869

Autor: Fateme Moslehi, Masoud Sattari, Alireza Shenavar Masouleh

Publikováno v: International Journal of Aquatic Biology, Vol 4, Iss 1, Pp 11-16 (2016)

An eight-week experiment was carried out to determine the effects of dietary Pediococcus pentosaceus as probiotic on the body composition and gut microbiota of Siberian sturgeon, Acipenser baerii. A total of 180 fish with mean body weight of 143±0.0

Externí odkaz: https://doaj.org/article/43f51ee11ba84ac3a2abe6dad60723c7

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A hybrid reciprocal model of PCA and K-means with an innovative approach of considering sub-datasets for the improvement of K-means initialization and step-by-step labeling to create clusters with high interpretability

Autor: Abdorrahman Haeri, Fateme Moslehi, Seyed Alireza Mousavian Anaraki

Publikováno v: Pattern Analysis and Applications. 24:1387-1402

The K-means algorithm is a popular clustering method, which is sensitive to the initialization of samples and selecting the number of clusters. Its performance on high-dimensional datasets is considerably influenced. Principal component analysis (PCA

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6f8ee324f63f39c905794443dcd6efc6
https://doi.org/10.1007/s10044-021-00977-x

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A novel feature selection approach based on clustering algorithm

Autor: Fateme Moslehi, Abdorrahman Haeri

Publikováno v: Journal of Statistical Computation and Simulation. 91:581-604

Clustering is one of the main methods of data mining. K-means algorithm is one of the most common clustering algorithms due to its efficiency and ease of use. In many data mining issues, the datase...

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1791c6b80ff34d486c92780130d6ecbf
https://doi.org/10.1080/00949655.2020.1822358

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An evolutionary computation-based approach for feature selection

Autor: Fateme Moslehi, Abdorrahman Haeri

Publikováno v: Journal of Ambient Intelligence and Humanized Computing. 11:3757-3769

Feature selection plays an important role in the classification process to decrease the computational time, which can reduce the dimensionality of a dataset and improve the accuracy and efficiency of a machine learning task. Feature selection is a pr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ca651554fc52949710f8563e95c782d7
https://doi.org/10.1007/s12652-019-01570-1

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A novel hybrid GA–PSO framework for mining quantitative association rules

Autor: Abdorrahman Haeri, Francisco Martínez-Álvarez, Fateme Moslehi

Publikováno v: Soft Computing. 24:4645-4666

Discovering association rules is a useful and common technique for data mining in which dependencies among datasets are shown. Discovering the rules from continuous numeric datasets is one of the common challenges in data mining. Furthermore, another

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7b8607e3294b1f80b6c08d5097a0aa2a
https://doi.org/10.1007/s00500-019-04226-6

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A novel hybrid wrapper–filter approach based on genetic algorithm, particle swarm optimization for feature subset selection

Autor: Fateme Moslehi, Abdorrahman Haeri

Publikováno v: Journal of Ambient Intelligence and Humanized Computing. 11:1105-1127

The classification is one of the main technique of machine learning science. In many problems, the data sets have a high dimensionality that the existence of all features is not important to the purpose of the problem, and this will decrease the accu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c85761b4c3e7171333c137fe8aa60c94
https://doi.org/10.1007/s12652-019-01364-5

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A novel selective clustering framework for appropriate labeling of the clusters based on K-means algorithm

Autor: Fateme Moslehi, Mohammad Reza Gholamian, Abdorrahman Haeri

Publikováno v: Scientia Iranica.

Clustering is one of the main methods of data mining. K-means algorithm is one of the most common clustering algorithms due to its efficiency and ease of use. One of the challenges of clustering is to identify the appropriate label for each cluster.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a469b09be37269fad1e06f1503e0d98c
https://doi.org/10.24200/sci.2019.51110.2010

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