Results 221 to 230 of about 312,403 (279)

Machine Learning-Driven Prediction of Manufacturing Parameters and Analysis of Mechanical Properties of PC-ABS Specimens Produced by the Fused Deposition Modeling Additive Manufacturing Method. [PDF]

Polymers (Basel)
Pazarcıkcı A, Özsoy K, Aksoy B.
europepmc   +1 more source

A Machine Learning Approach to Predicting Household Smoke Exposure Risk in Somalia: An Analysis With SHAP Explanations. [PDF]

Environ Health Insights
Omar MA, Hassan YSA, Ali AS, Ahmed MM.
europepmc   +1 more source

Joint Damage Prediction in Non-Severe Hemophilia A with Artificial Intelligence. [PDF]

J Blood Med
Marco-Rico A, Calvo-Villas JM, Lopez-Jaime FJ, Canaro Hirnyk M, Nieto-Hernández MDM, Herrero Martín S, Entrena-Ureña L, Marcellini-Antonio S, Diaz-Jordan BL, Jurado-Herrera S, Pérez-González NF, García-Díaz C, García-Candel F, Fernández-Bello I, Mateo-Sotos J, Marco-Vera P.   +15 more
europepmc   +1 more source

Geographic authentication of <i>Amomum tsaoko</i> seeds using fourier transform-near infrared spectroscopy combined with machine learning techniques and feature reduction analysis. [PDF]

Front Plant Sci
Zheng Y, Lan S, Hu H, Huang X, Wang H, Cao H, Liu X, Yang Y, Ji S, Xie H.   +9 more
europepmc   +1 more source

AbDist: a lightweight, distance-based model for antibody affinity prediction as an interpretable benchmark for machine learning models. [PDF]

MAbs
Hoffstedt M, Wowra J, Wätzig H, Baumann K.   +3 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Improved k-nearest neighbor classification

Pattern Recognition, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, Yingquan, Ianakiev, Krassimir, Govindaraju, Venu   +2 more
openaire   +2 more sources

K-Nearest Neighbors Hashing

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Hashing based approximate nearest neighbor search embeds high dimensional data to compact binary codes, which enables efficient similarity search and storage. However, the non-isometry sign() function makes it hard to project the nearest neighbors in continuous data space into the closest codewords in discrete Hamming space.
Xiangyu He, Peisong Wang, Jian Cheng
openaire   +1 more source

k-Nearest Neighbor Classification

2009
The k-nearest neighbor (k-NN) method is one of the data mining techniques considered to be among the top 10 techniques for data mining [237]. The k-NN method uses the well-known principle of Cicero pares cum paribus facillime congregantur (birds of a feather flock together or literally equals with equals easily associate).
Antonio Mucherino, Petraq J. Papajorgji, Panos M. Pardalos   +2 more
openaire   +2 more sources

K-Nearest Neighbors

2023
  +6 more sources