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LogitBoost
In machine learning and computational learning theory, LogitBoost is a boosting algorithm formulated by Jerome Friedman, Trevor Hastie, and Robert…
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AdaBoost
Boosting (machine learning)
BrownBoost
Computational learning theory
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Broader (1)
Ensemble learning
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Evaluación de proyectos usando sistemas basados en algoritmos genéticos de aprendizaje de reglas
Alain Guerrero Enamorado
,
Iliana Perez Pupo
,
S. Ventura
,
C. Morell
,
P. P. Pérez
2017
Corpus ID: 67345847
In the present work is assessed the behavior of the evolutionary algorithm MCGEP in different versions of a project management…
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2016
2016
An Efficient Smooth Quantile Boost Algorithm for Binary Classification
Zhefeng Wang
,
Wanzhou Ye
2016
Corpus ID: 55190864
In this paper, we propose a Smooth Quantile Boost Classification (SQBC) algorithm for binary classification problem. The SQBC…
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2016
2016
Non-Convex Potential Function Boosting Versus Noise Peeling : - A Comparative Study
Viktor Venema
2016
Corpus ID: 210170249
In recent decades, boosting methods have emerged as one of the leading ensemble learning techniques. Among the most popular…
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2014
2014
Application of Classification Restricted Boltzmann Machine with discriminative and sparse learning to medical domains
J. Tomczak
2014
Corpus ID: 15263139
Recent developments have demonstrated deep models to be very powerful generative models which are able to extract features…
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2013
2013
An Application of the Logitboost Ensemble Algorithm in Loan Appraisals
Z. Kirori
,
J. Ogutu
Intelligent Information Systems
2013
Corpus ID: 28518820
Mitigation of credit risk is a key aspect of portfolio management in any financial institution. This is primarily due to…
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2013
2013
Protein Fold Classification Using Sequence Features
R. Paper
,
T. Sravani
,
K. Vani
2013
Corpus ID: 212526268
—Protein fold classification is one of the challenging problems in bioinformatics. It classifies the protein fold in the given…
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2012
2012
SNMiner : A Rapid Evaluator of Anomaly Detection Accuracy in Sensor Networks
Giovani Rimon Abuaitah
,
Bin Wang
2012
Corpus ID: 11147226
Modeling faults and malicious activities in sensor network s can be challenging. Designing and re-evaluating a “good” classifier…
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2007
2007
Automatic Recognition of Craters on the Surface of Mars Based on Boosting Techniques
R. Martins
,
J. Marques
,
P. Pina
,
Margarida Silveira
2007
Corpus ID: 31336281
The identification of impact craters on a planetary surface has crucial importance for planetary studies because it allows the…
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2007
2007
Denial of Information Attacks in Event Processing
C. Pu
Event Processing
2007
Corpus ID: 2600116
It is a common assumption in event processing that the events are A¢â‚¬A“cleanA¢â‚¬Â, i.e., they come from well-behaved and…
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2006
2006
Kernel Feature Selection to Improve Generalization Performance of Boosting Classifiers
Kenji Nishida
,
Takio Kurita
International Conference on Image Processing…
2006
Corpus ID: 10213542
In this paper, kernel feature selection is proposed to improve generalization performance of boosting classifiers. Kernel feature…
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