Results 171 to 180 of about 23,652 (302)

Best-first search-based approach for mining top-k closed frequent itemsets from uncertain databases. [PDF]

PLoS One
Le N, Vo H, Nguyen T.
europepmc   +1 more source

Mining Frequent Closed Itemsets with the Frequent Pattern List

, 2008
The mining of the complete set of frequent itemsets will lead to a huge number of itemsets. Fortunately, this problem can be reduced to the mining of frequent closed itemsets (FCIs), which results in a much smaller number of itemsets.
Ching-chi Hsu, Henry Chen, Fan-chen Tseng   +2 more
core  

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

Scalable discovery of spatial multicellular patterns via neighborhood-to-sequence transformation. [PDF]

Commun Biol
Zhao F, Wang S, Wang Z, Cui Y, Zhao Y, Yuan Z.   +5 more
europepmc   +1 more source

Sequential Pattern Mining and Nonmonotonic Reasoning for Intelligent Information Agents

, 2012
[[abstract]]With the explosive growth of information available on the Internet, more effective data mining and data reasoning mechanism is required to process the sheer volume of information. Belief revision logic offers the expressive power to represent
吳勝堂;Wu, Sheng-Tang
core  

Automatic Determination of Quasicrystalline Patterns from Microscopy Images

Advanced Intelligent Discovery, EarlyView.
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender, Marco Corrias, Cesare Franchini   +2 more
wiley   +1 more source

Frequent Pattern Mining [PDF]

, 2018
openaire   +1 more source

CLTD-LP: an optimized top-down clustering approach with linear prefix trees for scalable frequent pattern discovery in large datasets. [PDF]

Sci Rep
Sinthuja M, Diviya M, Saranya P.
europepmc   +1 more source