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Shedding light on the asymmetric learning capability of AdaBoost
2012
Pattern Recognition Letters
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A novel class-conditional description of AdaBoost, which models the actual asymmetric behavior of the algorithm, is presented. ...
This analysis reveals that, beyond some preconceptions, AdaBoost can be directly used as an asymmetric learning algorithm, preserving all its theoretical properties. ...
other (they are definetely useless), so we think that some light must be shed in order to clarify the actual asymmetric learning capabilities of AdaBoost. ...
doi:10.1016/j.patrec.2011.10.022
fatcat:idxwq7dqg5gq5phvbxr2a6gi6i
Untangling AdaBoost-based Cost-Sensitive Classification. Part I: Theoretical Perspective
[article]
2016
arXiv
pre-print
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In the last few years, a lot of approaches have been proposed to provide standard AdaBoost with cost-sensitive capabilities, each with a different focus. ...
on a common basis. ...
Our final goal is finding a definitive scheme to directly translate any cost-sensitive learning problem to the AdaBoost framework and shedding light on which algorithm can ensure the best performance. ...
arXiv:1507.04125v2
fatcat:xpap2gzzvzcmhdgiavsl34zjym
Circ-LocNet: A Computational Framework for Circular RNA Sub-Cellular Localization Prediction
2022
International Journal of Molecular Sciences
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Like other non-coding RNAs, sub-cellular localization knowledge of circRNAs has the aptitude to demystify the influence of circRNAs on protein synthesis, degradation, destination, their association with ...
To complement wet-lab experiments, considering the progress made by machine learning approaches for the determination of sub-cellular localization of other non-coding RNAs, the paper in hand develops a ...
It also sheds light on the collection and preparation of benchmark dataset and evaluation metrics used to assess the performance of Circ-LocNet framework. ...
doi:10.3390/ijms23158221
pmid:35897818
pmcid:PMC9329987
fatcat:zg7zsov7pvcoxgswvqc2co6yuu
Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors)
2000
Annals of Statistics
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Boosting is one of the most important recent developments in classification methodology. ...
This approach, based on best-first truncated tree induction, often leads to better performance, and can provide interpretable descriptions of the aggregate decision rule. ...
We thank Andreas Buja for alerting us to the recent work on text classification at AT&T laboratories, Bogdan Popescu for illuminating discussions on PAC learning theory and Leo Breiman and Robert Schapire ...
doi:10.1214/aos/1016218223
fatcat:gmganzhqxbdjpoa4zbwyiv47ge
Machine Learning for Quantitative Finance Applications: A Survey
2019
Applied Sciences
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This paper proposes a review of some of the most significant works providing an exhaustive overview of recent machine learning (ML) techniques in the field of quantitative finance showing that these methods ...
In the past few decades, researchers have proposed several systems based on traditional approaches, such as autoregressive integrated moving average (ARIMA) and the exponential smoothing model, in order ...
In this paper, we shed light on the promising results achieved by machine learning approaches for time-series forecasting in the financial sector. ...
doi:10.3390/app9245574
fatcat:x5g2vrzovfcijlfjxmej4fo5nu
Human Face Detection Techniques: A Comprehensive Review and Future Research Directions
2021
Electronics
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However, there is little attention paid in making a comprehensive survey of the available algorithms. This paper aims at providing fourfold discussions on face detection algorithms. ...
The recent veer proliferation of computational resources is paving the way for frantic advancement of face detection technology. Many astutely developed algorithms have been proposed to detect faces. ...
Additionally, future research needs to shed further light on how to manage efficient parallel processing closer to the end devices. ...
doi:10.3390/electronics10192354
fatcat:oy7adwj6cjefnm66cn5kxrybni
A Preliminary Study of FTIR Spectroscopy as a Potential Non-Invasive Screening Tool for Pediatric Precursor B Lymphoblastic Leukemia
2021
Molecules
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); an AdaBoost-based predictive model for classifying healthy vs. ...
The most important include: the different peak area ratio 2965/1645 cm−1 (p = 0.002); the lower average percentage of both β-sheet and β-turn protein structures in the sera of BCP-ALL patients (p = 0.03 ...
Data Availability Statement: The data presented in this study is available in Supplementary Materials.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/molecules26041174
pmid:33671817
pmcid:PMC7926870
fatcat:taitiw44gnbl3k7eoym7iokvd4
Checking account activity and credit default risk of enterprises: An application of statistical learning methods
[article]
2017
arXiv
pre-print
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The existence of asymmetric information has always been a major concern for financial institutions. ...
As one of the major commercial banks in France, we have access to the the account activities of corporate clients. ...
We had a thorough discussion on the mechanisms of these methods which have significant implications on the results. ...
arXiv:1707.00757v1
fatcat:jagpybr7kng4fki3qmgdjse7gm
Computer-based Approach to Detect Wrinkles and Suggest Facial Fillers
2019
International Journal of Advanced Computer Science and Applications
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Before feeding the images into the deep learning Inception model for classifying whether the face foreheads have wrinkles or no wrinkles, an image cropping process is required. ...
The Inception model is the core of the framework. ...
ACKNOWLEDGMENT "Portions of the research in this paper use the FERET database of facial images collected under the FERET program, sponsored by the DOD Counterdrug Technology Development Program Office" ...
doi:10.14569/ijacsa.2019.0100941
fatcat:z34h74677fezzhjljkixztploy
A Seed-Guided Latent Dirichlet Allocation Approach to Predict the Personality of Online Users Using the PEN Model
2022
Algorithms
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This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY ...
Conflicts of Interest: The authors declare no conflict of interest. ...
Acknowledgments: The research team want to thank Universiti Sains Malaysia for providing fund and technical supports for this experiment. ...
doi:10.3390/a15030087
dblp:journals/algorithms/SagadevanMH22
fatcat:kkecjlosmneupilhrjknvf4a34
Cryptocurrencies and Artificial Intelligence: Challenges and Opportunities
2020
IEEE Access
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Contents of the research are solely the responsibility of the authors and do not necessarily represent the official views of the Qatar National Research Fund (QNRF). ...
ACKNOWLEDGMENT This publication was made possible by a grant from the Qatar National Research Fund (QNRF); project number NPRP X-063-1-014. ...
The discussion in their work sheds more light on the cryptocurrency market investors and the herd behavior shown by one cluster which results in speculative price changes. ...
doi:10.1109/access.2020.3025211
fatcat:awjyqt5p2veg5ld2lqqm527lgq
A Comprehensive Survey for Intelligent Spam Email Detection
2019
IEEE Access
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Based on the number the relevance of an emerging intelligent method, papers representing each method were identified, read, and summarized. ...
like email and IP address of each sender and recipient of where the email originated and what stopovers, and final destination. ...
calculations may shed some light on the underlying cause. ...
doi:10.1109/access.2019.2954791
fatcat:ikt6cayggbb2dkrm52fxzz2dqm
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 results of employing a deep network for operational risk forecasting confirm the feature learning capability of deep learning, provide guidance on designing a suitable network architecture and demonstrate ...
Conventional machine learning requires data that is representative of the feature-target relationship and relies on the often costly development, maintenance, and revision of handcrafted features. ...
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
EMMA: An Emotion-Aware Wellbeing Chatbot
[article]
2019
arXiv
pre-print
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2018 pre-print arXiv:1812.11423v1 fatcat:fznycspvpbcrneqprwmddjel3u
Our results show that our personalized machine learning model was perceived as likable via self-reports of emotion from users. ...
Furthermore, the feasibility of automating the delivery of just-in-time mHealth interventions via such an agent has not been fully studied. ...
Also, the open responses shed light on what could be improved. ...
arXiv:1812.11423v2
fatcat:qbn5axlbwndb7ej7euwouh4g4e
Automated Facial Action Coding System for dynamic analysis of facial expressions in neuropsychiatric disorders
2011
Journal of Neuroscience Methods
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We created temporal AU profiles that provided rich information on the dynamics of facial muscle movements for each subject. ...
The quantitative measures of flatness and inappropriateness showed clear differences between patients and the controls, highlighting their potential in automatic and objective quantification of symptom ...
AU combinations measure the simultaneous activation of multiple facial muscles, which will shed light on the role of synchronized facial muscle movement in facial expressions of healthy controls and patients ...
doi:10.1016/j.jneumeth.2011.06.023
pmid:21741407
pmcid:PMC3402717
fatcat:fdsyzkthorgkbcpgpvtdffgwxq
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