Results 51 to 60 of about 2,759,833 (308)
Hybrid feature selection based ScC and forward selection methods [PDF]
International Journal of Data and Network ScienceOperational data is always huge. A preprocessing step is needed to prepare such data for the analytical process so the process will be fast. One way is by choosing the most effective features and removing the others. Feature selection algorithms
Luai Al-Shalabi
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Optimal Feature Aggregation and Combination for Two-Dimensional Ensemble Feature Selection
Information, 2020 Feature selection is a way of reducing the features of data such that, when the classification algorithm runs, it produces better accuracy. In general, conventional feature selection is quite unstable when faced with changing data characteristics.
Machmud Roby Alhamidi, Wisnu Jatmiko
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Special Issue “Algorithms for Feature Selection”
Algorithms, 2023 This Special Issue of the open access journal Algorithms is dedicated to showcasing cutting-edge research in algorithms for feature selection [...]
Muhammad Adnan Khan
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CCT4 promotes tunneling nanotube formation
FEBS Letters, EarlyView.Tunneling nanotubes (TNTs) are membranous tunnel‐like structures that transport molecules and organelles between cells. They vary in thickness, and thick nanotubes often contain microtubules in addition to actin fibers. We found that cells expressing monomeric CCT4 generate many thick TNTs with tubulin.
Miyu Enomoto +3 more
wiley +1 more source
Bayesian reordering model with feature selection
, 2014 In phrase-based statistical machine translation systems, variation in grammatical structures between source and target languages can cause large movements of phrases.
Alrajeh, Abdullah, Niranjan, Mahesan
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FEBS Letters, EarlyView.Phototrophs evolved light‐harvesting systems adapted for efficient photon capture in habitats enriched in far‐red radiation. A subset of eukaryotic pigment‐binding proteins can absorb far‐red photons via low‐energy chlorophyll states known as red forms.
Antonello Amelii +8 more
wiley +1 more source
Infinite Latent Feature Selection Technique for Hyperspectral Image Classification
Jurnal Elektronika dan Telekomunikasi, 2019 The classification process is one of the most crucial processes in hyperspectral imaging. One of the limitations in classification process using machine learning technique is its complexities, where hyperspectral image format has a thousand band that can
Tajul Miftahushudur +2 more
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Penerapan Ensemble Feature Selection dan Klasterisasi Fitur pada Klasifikasi Dokumen Teks [PDF]
, 2013 An ensemble method is an approach where several classifiers are created from the training data which can be often more accurate than any of the single classifiers, especially if the base classifiers are accurate and different one each other.
Aryuni, M. (Mediana)
core
Rad27/FEN1 prevents accumulation of Okazaki fragments and ribosomal DNA copy number changes
FEBS Letters, EarlyView.The budding yeast Rad27 is a structure‐specific endonuclease. Here, the authors reveal that Rad27 is crucial for maintaining the stability of the ribosomal RNA gene (rDNA) region. Rad27 deficiency leads to the accumulation of Okazaki fragments and changes in rDNA copy number.
Tsugumi Yamaji +3 more
wiley +1 more source
Entropy-based feature selection with applications to industrial internet of things (IoT) and breast cancer prediction [PDF]
Big Data and Computing VisionsFeature Selection (FS) is employed in the Machine Learning (ML) process to increase accuracy. Eliminating redundant and irrelevant variables while keeping the most important ones boosts the prediction capacity of the algorithms.
Ismail Mageed
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