Results 81 to 90 of about 73,492 (280)

Trigonometric words ranking model for spam message classification

IET Networks, EarlyView., 2022
Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi, Ali Hakem Alsaeedi, Dhiah Al‐Shammary, Zaid Abdi Alkareem Alyasseri, Mazin Abed Mohammed, Karrar Hameed Abdulkareem, Riyadh Rahef Nuiaa, Mustafa Musa Jaber   +7 more
wiley   +1 more source

Classifying with the Fine Structure of Distributions: Leveraging Distributional Information for Robust and Plausible Naïve Bayes

Machine Learning and Knowledge Extraction
In machine learning, the Bayes classifier represents the theoretical optimum for minimizing classification errors. Since estimating high-dimensional probability densities is impractical, simplified approximations such as naïve Bayes and k-nearest ...
Quirin Stier, Jörg Hoffmann, Michael C. Thrun   +2 more
doaj   +1 more source

PREDIKSI PENYAKIT GINJAL KRONIS MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIER BERBASIS PARTICLE SWARM OPTIMIZATION

Jurnal Tekno Insentif, 2019
Abstrak - Penyakit ginjal kronis (PGK) merupakan masalah kesehatan masyarakat global dengan prevalensi dan insiden gagal ginjal yang meningkat, prognosis yang buruk dan biaya yang tinggi.
Toni Arifin, Daniel Ariesta
doaj   +1 more source

A Naive Bayes Classifier for Protein Function Prediction

In Silico Biology: Journal of Biological Systems Modeling and Multi-Scale Simulation, 2009
A Naive Bayes classifier tool is presented for annotating proteins on the basis of amino acid motifs, cellular localization and protein-protein interactions. Annotations take the form of posterior probabilities within the Molecular Function hierarchy of the Gene Ontology (GO).
Jukka, Kohonen, Sarish, Talikota, Jukka, Corander, Petri, Auvinen, Elja, Arjas   +4 more
openaire   +2 more sources

An artificial neural network–based deep learning model to predict combined stress impact and interaction in plants

Applications in Plant Sciences, EarlyView.
Abstract Premise Plants are frequently exposed to combinations of abiotic and biotic stresses that pose a greater threat to yield and productivity than individual stresses. However, knowledge of the impact of many stress combinations in numerous plants is limited due to the lack of experimental data, which could take decades to generate.
Piyush Priya, Prachi Pandey, Rubi Jain, Manu Kandpal, Shradha Jain, Rim Chaudhury, Venkategowda Ramegowda, Muthappa Senthil‐Kumar   +7 more
wiley   +1 more source

Parametric design method of building structured cabling system oriented to data mining

IET Networks, EarlyView., 2022
This paper puts forward the method of secondary development and design software through the research of building structured cabling system (SCS), and uses data mining technology to carry out parametric design of building SCS. Then, the feasibility of the design is tested by comparing the data of the traditional design and the parametric design ...
Bing Wang, Wei Yue
wiley   +1 more source

Chemical named entity recognition in the texts of scientific publications using the naïve Bayes classifier approach. [PDF]

J Cheminform, 2022
Tarasova OA, Rudik AV, Biziukova NY, Filimonov DA, Poroikov VV.   +4 more
europepmc   +2 more sources

Effects of Cellulase and Lactobacillus plantarum Supplementation on Fermentation Characteristics, In Situ Degradability, and Microbial Community Dynamics of Apple Pomace Silage

Animal Research and One Health, EarlyView.
This study aimed to investigate the effects of cellulase and Lactobacillus plantarum on the silage quality, in situ digestibility, and microbial communities of apple pomace silage. The combined supplementation of cellulase and Lactobacillus plantarum in apple pomace silage improved fermentation quality and enhanced rumen utilization efficiency.
Zhuangzhuang Liu, Xiongfei Zhang, Fengbo Sun, Junhu Yao, Xinjian Lei   +4 more
wiley   +1 more source

Altitude Training: Strong Bounds for Single-Layer Dropout [PDF]

, 2014
Dropout training, originally designed for deep neural networks, has been successful on high-dimensional single-layer natural language tasks. This paper proposes a theoretical explanation for this phenomenon: we show that, under a generative Poisson topic
Fithian, William, Liang, Percy, Wager, Stefan, Wang, Sida   +3 more
core   +1 more source

Digital Technologies Disclosure and the Cost of Capital: The Mediating Role of Sustainability Performance

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines the economic consequences of Digital Technologies Disclosure (DTD), focusing on its impact on the cost of capital. The increasing significance of digital transformation in shaping corporate strategies and market perceptions motivates the study.
Hussein Mohsen Saber Ahmed, Awad Elsayed Awad Ibrahim, Khaldoon Albitar   +2 more
wiley   +1 more source