Results 41 to 50 of about 794 (166)
A Design‐Driven Machine Learning Approach for Invariant Mining in a Smart Grid
An ICS is vulnerable to cyber‐attacks arising from within its communication network or directly from the SCADA and devices such as PLCs. The study reported here presents a scenario‐specific invariant mining approach to detect anomalies in plant behaviour.
Danish Hudani +5 more
wiley +1 more source
Proposed Algorithm for Extracting Association Rule Depend on Closed Frequent Itemset (EACFI) [PDF]
Association rules are important one of data mining activities. All algorithms of association rule mining consist of finding frequency of itemsets, which satisfy a minimum support threshold, and then compute confidence percentage for each k-itemsets to ...
Emad k. Jbbar, Yaser Munther
doaj +1 more source
ABSTRACT Urban bus accidents present major safety and operational challenges, particularly in densely populated metropolitan areas. This study develops a machine learning‐based analytical framework to identify, quantify, and interpret the factors associated with severe bus accidents.
Bowei Chen +3 more
wiley +1 more source
Efficient Associate Rules Mining Based on Topology for Items of Transactional Data
A challenge in association rules’ mining is effectively reducing the time and space complexity in association rules mining with predefined minimum support and confidence thresholds from huge transaction databases.
Bo Li, Zheng Pei, Chao Zhang, Fei Hao
doaj +1 more source
The purpose of this study was to explore the risk factors for autonomous vehicle (AV) crashes and their interdependencies. A total of 659 AV crash data were collected between 2018 and July 2024 from AV crash reports published by the California Department of Motor Vehicles.
Tao Wang +4 more
wiley +1 more source
ABSTRACT Machine learning techniques are increasingly used for high‐stakes decision‐making, such as college admissions, loan attribution, or recidivism prediction. Thus, it is crucial to ensure that the models learnt can be audited or understood by human users, do not create or reproduce discrimination or bias and do not leak sensitive information ...
Julien Ferry +4 more
wiley +1 more source
A Fast Approach for Up-Scaling Frequent Itemsets
With the rapid growth of data scale and diversification of demand, people have an urgent desire to extract useful frequent itemset from datasets of different scales. It is no doubt that the traditional method can solve the problem.
Runzi Chen, Shuliang Zhao, Mengmeng Liu
doaj +1 more source
Content Validity of Creativity Self‐Report Questionnaires From PISA 2022
ABSTRACT The present paper questions the content validity of the eight creativity‐related self‐report scales available in PISA 2022's context questionnaire and provides a set of considerations for researchers interested in using these indexes. Specifically, we point out some threats to the content validity of these scales (e.g., creative thinking self ...
B. Goecke, S. Weiss, B. Barbot
wiley +1 more source
Frequent Itemset Mining and Association Rules [PDF]
With the advent of mass storage devices, databases have become larger and larger. Point-of-sale data, patient medical data, scientific data, and credit card transactions are just a few sources of the ever-increasing amounts of data. These large datasets provide a rich source of useful information.
Imberman S., Tansel A.U.
openaire +3 more sources
Video Mining with Frequent Itemset Configurations [PDF]
We present a method for mining frequently occurring objects and scenes from videos. Object candidates are detected by finding recurring spatial arrangements of affine covariant regions. Our mining method is based on the class of frequent itemset mining algorithms, which have proven their efficiency in other domains, but have not been applied to video ...
Quack, Till +2 more
openaire +2 more sources

