Results 221 to 230 of about 505,761 (263)
Some of the next articles are maybe not open access.
Data imbalance in classification: Experimental evaluation
Information Sciences, 2020Abstract The advent of Big Data has ushered a new era of scientific breakthroughs. One of the common issues that affects raw data is class imbalance problem which refers to imbalanced distribution of values of the response variable. This issue is present in fraud detection, network intrusion detection , medical diagnostics, and a number of ...
Fadi Thabtah +2 more
exaly +2 more sources
Adjusting the imbalance ratio by the dimensionality of imbalanced data [PDF]
Pattern Recognition Letters, 2020 Class-imbalance extent metrics measure how imbalanced the data are. In pattern classification, it is usually expected that the higher the imbalance extent, the worse the classification performance, and thus an appropriate imbalance extent metric should show a negative correlation with the classification performance.
Rui Zhu, Yiwen Guo, Jing-Hao Xue
exaly +4 more sources
Imbalance-Aware Uplift Modeling for Observational Data
Proceedings of the AAAI Conference on Artificial Intelligence, 2022Uplift modeling aims to model the incremental impact of a treatment on an individual outcome, which has attracted great interests of researchers and practitioners from different communities. Existing uplift modeling methods rely on either the data collected from randomized controlled trials (RCTs) or the observational data which is more realistic ...
Xuanying Chen +9 more
openaire +1 more source
Effects of data imbalance on estimation of heritability
Theoretical and Applied Genetics, 1985Effects of data imbalance on bias, sampling variance and mean square error of heritability estimated with variance components were examined using a random two-way nested classification. Four designs, ranging from zero imbalance (balanced data) to "low", "medium" and "high" imbalance, were considered for each of four combinations of heritability (h(2)=0.
R F, Caro, M, Grossman, R L, Fernando
openaire +2 more sources
RHSBoost: Improving classification performance in imbalance data
Computational Statistics & Data Analysis, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Joonho Gong, Hyunjoong Kim
openaire +1 more source
Alleviating class imbalance problem in data mining
2013 21st Signal Processing and Communications Applications Conference (SIU), 2013The class imbalance problem in two-class data sets is one of the most important problems. When samples of one class in a training data set vastly outnumber samples of the other class, standard machine learning algorithms tend to be overwhelmed by the majority class and ignore the minority class.
Akkenzhe Sarmanova, Songul Albayrak
openaire +2 more sources
Evolutionary data analysis for the class imbalance problem
Intelligent Data Analysis, 2010Class imbalance, where the classes in a dataset are not represented equally, is a common occurrence in machine learning. Classification models built with such datasets are often not practical since most machine learning algorithms would tend to perform poorly on the minority class instances.
Taghi M. Khoshgoftaar +2 more
openaire +1 more source
A dissimilarity-based imbalance data classification algorithm
Applied Intelligence, 2014Class imbalances have been reported to compromise the performance of most standard classifiers, such as Naive Bayes, Decision Trees and Neural Networks. Aiming to solve this problem, various solutions have been explored mainly via balancing the skewed class distribution or improving the existing classification algorithms.
Xueying Zhang +5 more
openaire +1 more source
Transient Detection Modeling as Imbalance Data Classification
2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII), 2018Acquisition of large astronomical data prompted astronomers to join the global trend of big data science and artificial intelligence. The Gravitational-wave Optical Transient Observers is a visual counterpart in capturing transient events provides millions of observed sources which are then systematically process and analyze in reference to simulated ...
Aireen B. Tabacolde +5 more
openaire +1 more source