Churn prediction in Turkey's telecommunications sector: A proposed multiobjective–cost‐sensitive ant colony optimization
Sign Up to like & getrecommendations! Published in 2020 at "Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"
DOI: 10.1002/widm.1338
Abstract: Players in the telecommunications sector struggle against the competition to keep customers, and therefore they need effective churn management. Most classification algorithms either ignore misclassification cost or assume that the costs of all incorrect classification… read more here.
Keywords: telecommunications sector; cost; churn prediction; cost sensitive ... See more keywords
Tri-partition cost-sensitive active learning through kNN
Sign Up to like & getrecommendations! Published in 2019 at "Soft Computing"
DOI: 10.1007/s00500-017-2879-x
Abstract: Active learning differs from the training–testing scenario in that class labels can be obtained upon request. It is widely employed in applications where the labeling of instances incurs a heavy manual cost. In this paper,… read more here.
Keywords: region; tri partition; active learning; cost ... See more keywords
Spam detection on social networks using cost-sensitive feature selection and ensemble-based regularized deep neural networks
Sign Up to like & getrecommendations! Published in 2019 at "Neural Computing and Applications"
DOI: 10.1007/s00521-019-04331-5
Abstract: Spam detection on social networks is increasingly important owing to the rapid growth of social network user base. Sophisticated spam filters must be developed to deal with this complex problem. Traditional machine learning approaches such… read more here.
Keywords: social network; network; neural networks; network spam ... See more keywords
Prediction of diagnosis results of rheumatoid arthritis patients based on autoantibodies and cost-sensitive neural network
Sign Up to like & getrecommendations! Published in 2022 at "Clinical Rheumatology"
DOI: 10.1007/s10067-022-06109-y
Abstract: To analyze and evaluate the effectiveness of the detection of single autoantibody and combined autoantibodies in patients with rheumatoid arthritis (RA) and related autoimmune diseases and establish a machine learning model to predict the disease… read more here.
Keywords: diagnosis; neural network; sensitive neural; model ... See more keywords
Imbalanced fault diagnosis of rotating machinery via multi-domain feature extraction and cost-sensitive learning
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Intelligent Manufacturing"
DOI: 10.1007/s10845-019-01522-8
Abstract: Fault diagnosis plays an essential role in rotating machinery manufacturing systems to reduce their maintenance costs. How to improve diagnosis accuracy remains an open issue. To this end, we develop a novel framework through combined… read more here.
Keywords: feature; diagnosis; cost sensitive; sensitive learning ... See more keywords
A cost-sensitive rotation forest algorithm for gene expression data classification
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DOI: 10.1016/j.neucom.2016.09.077
Abstract: Existing works show that the rotation forest algorithm has competitive performance in terms of classification accuracy for gene expression data. However, most existing works only focus on the classification accuracy and neglect the classification costs.… read more here.
Keywords: forest algorithm; classification; rotation forest; rotation ... See more keywords
"It's a mess sometimes": patient perspectives on provider responses to healthcare costs, and how informatics interventions can help support cost-sensitive care decisions
Sign Up to like & getrecommendations! Published in 2022 at "Journal of the American Medical Informatics Association : JAMIA"
DOI: 10.1093/jamia/ocac010
Abstract: OBJECTIVE We investigated patient experiences with medication- and test-related cost conversations with healthcare providers to identify their preferences for future informatics tools to facilitate cost-sensitive care decisions. MATERIALS AND METHODS We conducted 18 semistructured interviews… read more here.
Keywords: sensitive care; cost sensitive; cost conversations; informatics tools ... See more keywords
The OCS-SVM: An Objective-Cost-Sensitive SVM With Sample-Based Misclassification Cost Invariance
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2933437
Abstract: Studies on the traditional support vector machine (SVM) implicitly assume that the costs of different types of mistakes are the same and minimize the error rate. On the one hand, it is not enough for… read more here.
Keywords: svm sample; svm; sensitive svm; misclassification ... See more keywords
Cost-Sensitive Prediction of Stock Price Direction: Selection of Technical Indicators
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DOI: 10.1109/access.2019.2945907
Abstract: Stock market forecasting using technical indicators (TIs) is widely applied by investors and researchers. Using a minimal number of input features is crucial for successful prediction. However, there is no consensus about what constitutes a… read more here.
Keywords: technical indicators; tis; prediction; selection ... See more keywords
Network Intrusion Detection Based on Conditional Wasserstein Generative Adversarial Network and Cost-Sensitive Stacked Autoencoder
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3031892
Abstract: In the field of intrusion detection, there is often a problem of data imbalance, and more and more unknown types of attacks make detection difficult. To resolve above issues, this article proposes a network intrusion… read more here.
Keywords: network intrusion; intrusion detection; cost sensitive; network ... See more keywords
Cost-Sensitive Multitask Active Learning for Characterization of Urban Environments With Remote Sensing
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2018.2813436
Abstract: We propose a novel cost-sensitive multitask active learning (CSMTAL) approach. Cost-sensitive active learning (CSAL) methods were recently introduced to specifically minimize labeling efforts emerging from ground surveys. Here, we build upon a CSAL method but… read more here.
Keywords: active learning; multitask active; remote sensing; sensitive multitask ... See more keywords