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A Novel Example-Dependent Cost-Sensitive Stacking Classifier to Identify Tax Return Defaulters
2021
Business Information Systems
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This paper proposes a framework for an example-dependent cost-sensitive stacking classifier that uses cost-insensitive classifiers as base generalizers to make predictions on the input space. ...
Additionally, we develop an empirical study showing that our approach is more adept at identifying potential tax return defaulters than existing example-dependent cost-sensitive classification algorithms ...
To alleviate this problem, we propose a novel framework for example-dependent cost-sensitive stacked classifiers that give a competitive model performance and increased savings compared to cost-insensitive ...
doi:10.52825/bis.v1i.61
fatcat:3zsm7wfd4vemzemlornjgswryu
Can Deep Learning Predict Risky Retail Investors? A Case Study in Financial Risk Behavior Forecasting
[article]
2019
arXiv
pre-print
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The paper examines the potential of deep learning to support decisions in financial risk management. ...
Deep learning promises a remedy. ...
Teunter, for his efforts in handling our paper and are thankful to three anonymous reviewers whose feedback has helped tremendously to improve earlier versions of the paper. ...
arXiv:1812.06175v3
fatcat:aswsbfb4xrbozellaic7fireom
Ensemble Model of the Financial Distress Prediction in Visegrad Group Countries
2021
Mathematics
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Five variables were selected as significant predictors in the model: current ratio, return on equity, return on assets, debt ratio, and net working capital. ...
Moreover, the ensemble model is a new technique in the Visegrad Group (V4) compared with other prediction models. ...
The results identify non-default and default companies. If the default probability is more than 50%, the company is a non-prosperous entity. ...
doi:10.3390/math9161886
fatcat:zmwih2vzzzgsnlvcjgy3ccl62a
One-class classification: taxonomy of study and review of techniques
2014
Knowledge engineering review (Print)
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This unique situation constrains the learning of efficient classifiers by defining class boundary just with the knowledge of positive class. ...
One-class classification (OCC) algorithms aim to build classification models when the negative class is either absent, poorly sampled or not well defined. ...
The value of the threshold (default 1.0) can be changed to either higher or lower values to change the detection sensitivity of the classifier. ...
doi:10.1017/s026988891300043x
fatcat:djdcvpij7jhs7gygtrtihq3dia
Machine Learning with a Reject Option: A survey
[article]
2021
arXiv
pre-print
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Finally, we provide examples of relevant application domains and show how machine learning with rejection relates to other machine learning research areas. ...
This machine learning subfield enables machine learning models to abstain from making a prediction when likely to make a mistake. ...
Finally, a trivial approach is to simply reject a default percentage of examples regardless of the testing dataset (Tax and Duin 2008; Denis and Hebiri 2020) . ...
arXiv:2107.11277v1
fatcat:hsatf7zp7re4vo52iyrbcllbzu
Investment: Fundamentals and Finance
1998
NBER macroeconomics annual
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+s ,B (+s+1 }=o =0
s =i \fc=i
/
subject to
16. For example, Moyen (1997) derives an equilibrium debt premium generated by default
costs.
17. ...
In a forward-looking model, investment depends on marginal Q, the present value of expected future marginal returns to capital. ...
doi:10.1086/ma.13.4623744
fatcat:wejsq2cam5d2hn6naiuvlulny4
Hunter in the Dark: Discover Anomalous Network Activity Using Deep Ensemble Network
[article]
2021
arXiv
pre-print
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However, existing designs achieve a high threat detection performance at the cost of a large number of false alarms, leading to alert fatigue. ...
It uses a deep ensemble network (trained through supervised learning) to detect anomalous network activities and exploits an unsupervised learning-based scheme to trim off mis-detection results. ...
While ML-based IDSs have a high capability of novel threat perception, existing designs achieve a high attack detection performance often at the cost of a large number of false alarms. ...
arXiv:2105.09157v4
fatcat:zkcteve4l5ezhfg5xetq5nku2y
Local Bank Financial Constraints and Firm Access to External Finance
2008
Journal of Finance
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Using novel data to measure risk and return on marginal lending, I show that the profitability of loans does not decline during lending expansions. ...
Using novel data to measure risk and return on marginal lending, I show that the profitability of loans does not decline during lending expansions. ...
For example, an increase in deposits might decrease the risk profile of the bank and reduce the cost of capital, or signal better future lending prospects and a higher marginal returns on lending. ...
doi:10.1111/j.1540-6261.2008.01393.x
fatcat:4qry6lw6znffrg7td34o5g5s4e
News-based trading strategies
2016
Decision Support Systems
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2018 pre-print arXiv:1807.06824v1 fatcat:4bcoitsxivh6bmzaiqnc72ejza
In this paper, we design trading strategies that utilize textual news in order to obtain profits on the basis of novel information entering the market. ...
Interestingly, this so-called news sentiment works fairly well in explaining stock returns. ...
These are then passed into a neural network to classify future performances. ...
doi:10.1016/j.dss.2016.06.020
fatcat:dw55lpgpebghrg5kyervzb4ljy
THE AMERICAN MUSEUM OF NATURAL HISTORY
1927
Science
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These commands switch jobs when a novel processor appears 20% faster than the one currently used. Success in phylogenetic analysis has become increasingly dependent on computational speed. ...
Dynamic programming (as in matrix characters above) is used to identify the best HTU sequences and determine cladogram cost. ...
Default = none autapomorphy An apomorphy unique to one taxon. ...
doi:10.1126/science.65.1672.31
fatcat:o6e4olz4qjbxjd5gc3daqoyzgm
THE AMERICAN MUSEUM OF NATURAL HISTORY
1911
Science
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These commands switch jobs when a novel processor appears 20% faster than the one currently used. Success in phylogenetic analysis has become increasingly dependent on computational speed. ...
Dynamic programming (as in matrix characters above) is used to identify the best HTU sequences and determine cladogram cost. ...
Default = none autapomorphy An apomorphy unique to one taxon. ...
doi:10.1126/science.33.839.142
pmid:17731786
fatcat:rktmdddq3jblpniceihkfymqji
THE AMERICAN MUSEUM OF NATURAL HISTORY
1903
Science
Preserved Fulltext
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These commands switch jobs when a novel processor appears 20% faster than the one currently used. Success in phylogenetic analysis has become increasingly dependent on computational speed. ...
Dynamic programming (as in matrix characters above) is used to identify the best HTU sequences and determine cladogram cost. ...
Default = none autapomorphy An apomorphy unique to one taxon. ...
doi:10.1126/science.17.439.874
pmid:17740807
fatcat:gq6kbw4cxffsrhdkwlap27zqga
The American Museum of Natural History
1870
Scientific American
Preserved Fulltext
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These commands switch jobs when a novel processor appears 20% faster than the one currently used. Success in phylogenetic analysis has become increasingly dependent on computational speed. ...
Dynamic programming (as in matrix characters above) is used to identify the best HTU sequences and determine cladogram cost. ...
Default = none autapomorphy An apomorphy unique to one taxon. ...
doi:10.1038/scientificamerican05141870-319
fatcat:oxbmiiy2x5gj5botnxdsoqo6om
American Museum of Natural History
1994
Nature
Preserved Fulltext
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These commands switch jobs when a novel processor appears 20% faster than the one currently used. Success in phylogenetic analysis has become increasingly dependent on computational speed. ...
Dynamic programming (as in matrix characters above) is used to identify the best HTU sequences and determine cladogram cost. ...
Default = none autapomorphy An apomorphy unique to one taxon. ...
doi:10.1038/369087b0
fatcat:daq5fif7fzg7lmrami6etrxco4
The American Museum of Natural History
1922
Nature
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The file type is application/pdf.
These commands switch jobs when a novel processor appears 20% faster than the one currently used. Success in phylogenetic analysis has become increasingly dependent on computational speed. ...
Dynamic programming (as in matrix characters above) is used to identify the best HTU sequences and determine cladogram cost. ...
Default = none autapomorphy An apomorphy unique to one taxon. ...
doi:10.1038/110880a0
fatcat:x2q5eso3bfempe7kike2ang5qa
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