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PREDICTION OF SOFTWARE ANOMALIES METHODS BASED ON ENSEMBLE LEARNING METHODS
Mağallaẗ Al-kūfaẗ Al-handasiyyaẗSoftware plays a vital role in all aspects of our daily lives, specifically in the fields of medicine and industry. In order to design high-quality and reliable software and avoid risks resulting from software errors, including physical and human errors,
Raghda Azad Hasan, Ibrahim Ahmed Saleh
doaj +1 more source
Learning Nonlinear Functions Using Regularized Greedy Forest
, 2013 We consider the problem of learning a forest of nonlinear decision rules with general loss functions. The standard methods employ boosted decision trees such as Adaboost for exponential loss and Friedman's gradient boosting for general loss.
Johnson, Rie, Zhang, Tong
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BoostFM: Boosted Factorization Machines for Top-N Feature-based Recommendation [PDF]
, 2017 Feature-based matrix factorization techniques such as Factorization Machines (FM) have been proven to achieve impressive accuracy for the rating prediction task. However, most common recommendation scenarios are formulated as a top-N item ranking problem
Chen, Long +5 more
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Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
Boosting Information Spread: An Algorithmic Approach
, 2017 The majority of influence maximization (IM) studies focus on targeting influential seeders to trigger substantial information spread in social networks.
Chen, Wei, Lin, Yishi, Lui, John C. S.
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Targeting p38α in cancer: challenges, opportunities, and emerging strategies
Molecular Oncology, EarlyView.p38α normally regulates cellular stress responses and homeostasis and suppresses malignant transformation. In cancer, however, p38α is co‐opted to drive context‐dependent proliferation and dissemination. p38α also supports key functions in cells of the tumor microenvironment, including fibroblasts, myeloid cells, and T lymphocytes.
Angel R. Nebreda
wiley +1 more source
Advances in Physics: X, 2019 Technological advancements enable collecting vast data, i.e., Big Data, in science and industry including biomedical field. Increased computational power allows expedient analysis of collected data using statistical and machine-learning approaches ...
Valeriy Gavrishchaka +2 more
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Frontiers in Public Health, 2020 A considerable amount of health record (HR) data has been stored due to recent advances in the digitalization of medical systems. However, it is not always easy to analyze HR data, particularly when the number of persons with a target disease is too ...
Koichi Fujiwara +6 more
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Development and Evaluation of Ensemble Learning Models for Detection of DDOS Attacks in IoT
Hittite Journal of Science and Engineering, 2022 Internet of Things that process tremendous confidential data have difficulty performing traditional security algorithms, thus their security is at risk.
Selim Buyrukoğlu, Yıldıran Yılmaz
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Generalized Boosting Algorithms for Convex Optimization [PDF]
, 2011 Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks, we analyze gradient-based descent algorithms for boosting with respect to ...
Bagnell, J. Andrew, Grubb, Alexander
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