Results 211 to 220 of about 112,373 (246)
Do More Open Economies Export Less Diversely in Brazilian Agribusiness?
Agribusiness, EarlyView.ABSTRACT This paper asks whether municipalities with a larger export‐to‐revenue ratio display a more concentrated bundle of exported goods in Brazilian agribusiness. Recent advances in export imputation for Brazilian municipalities allow for an analysis of the concentration profile of each municipality and its association with export openness.
Alan Leal, Michelle Marcia Viana Martins
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Vocal features based Parkinson's detection: An ensemble learning approach. [PDF]
MethodsXChakole M +5 more
europepmc +1 more source
Applying explainable artificial intelligence to interpret supervised ensemble learning models for robust credit card fraud detection. [PDF]
Sci RepAwad SS +3 more
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Diagnosis of SLAP lesions on shoulder MRI using a 2.5D deep learning and ensemble learning framework. [PDF]
Front SurgWang H +5 more
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Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2018
Ensemble methods are considered the state‐of‐the art solution for many machine learning challenges. Such methods improve the predictive performance of a single model by training multiple models and combining their predictions. This paper introduce the concept of ensemble learning, reviews traditional, novel and state‐of‐the‐art ensemble methods and ...
Lior Rokach
exaly +2 more sources
Ensemble methods are considered the state‐of‐the art solution for many machine learning challenges. Such methods improve the predictive performance of a single model by training multiple models and combining their predictions. This paper introduce the concept of ensemble learning, reviews traditional, novel and state‐of‐the‐art ensemble methods and ...
Lior Rokach
exaly +2 more sources
Frontiers of Computer Science, 2019
Despite significant successes achieved in knowledge discovery, traditional machine learning methods may fail to obtain satisfactory performances when dealing with complex data, such as imbalanced, high-dimensional, noisy data, etc. The reason behind is that it is difficult for these methods to capture multiple characteristics and underlying structure ...
Zhiwen Yu, Wenming Cao, Xibin Dong
exaly +2 more sources
Despite significant successes achieved in knowledge discovery, traditional machine learning methods may fail to obtain satisfactory performances when dealing with complex data, such as imbalanced, high-dimensional, noisy data, etc. The reason behind is that it is difficult for these methods to capture multiple characteristics and underlying structure ...
Zhiwen Yu, Wenming Cao, Xibin Dong
exaly +2 more sources
Transfer Learning and Ensemble Learning
2020In this chapter, we start from transfer learning and introduce the relationship between different learners; we use ensemble learning to combine them together and hope to get a strong learner from a weak learner by changing the training dataset or adjusting parameters of networks. Our ultimate goal is to implement a robust and stable classifier.
openaire +1 more source
Ensemble deep learning: A review
Engineering Applications of Artificial Intelligence, 2022Minghui Hu +2 more
exaly