A multi-instance ensemble learning model based on concept lattice

2011 ◽  
Vol 24 (8) ◽  
pp. 1203-1213 ◽  
Author(s):  
Xiangping Kang ◽  
Deyu Li ◽  
Suge Wang
Keyword(s):  
Ensemble Learning ◽  
Concept Lattice ◽  
Learning Model ◽  
Model Based

A Decomposition-Ensemble Learning Model Based on LSTM Neural Network for Daily Reservoir Inflow Forecasting

2019 ◽  
Vol 33 (12) ◽  
pp. 4123-4139 ◽  
Author(s):  
Yutao Qi ◽  
Zhanao Zhou ◽  
Lingling Yang ◽  
Yining Quan ◽  
Qiguang Miao
Keyword(s):  
Neural Network ◽  
Ensemble Learning ◽  
Learning Model ◽  
Model Based ◽  
Inflow Forecasting ◽  
Reservoir Inflow

scholarly journals A Heterogeneous Ensemble Learning Model Based on Data Distribution for Credit Card Fraud Detection

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yalong Xie ◽  
Aiping Li ◽  
Liqun Gao ◽  
Ziniu Liu
Keyword(s):  
Ensemble Learning ◽  
Credit Card ◽  
Data Distribution ◽  
Fraud Detection ◽  
Learning Model ◽  
Minority Class ◽  
Credit Card Fraud ◽  
Model Based ◽  
Savings Rate ◽  
Heterogeneous Ensemble

Credit card fraud detection (CCFD) is important for protecting the cardholder’s property and the reputation of banks. Class imbalance in credit card transaction data is a primary factor affecting the classification performance of current detection models. However, prior approaches are aimed at improving the prediction accuracy of the minority class samples (fraudulent transactions), but this usually leads to a significant drop in the model’s predictive performance for the majority class samples (legal transactions), which greatly increases the investigation cost for banks. In this paper, we propose a heterogeneous ensemble learning model based on data distribution (HELMDD) to deal with imbalanced data in CCFD. We validate the effectiveness of HELMDD on two real credit card datasets. The experimental results demonstrate that compared with current state-of-the-art models, HELMDD has the best comprehensive performance. HELMDD not only achieves good recall rates for both the minority class and the majority class but also increases the savings rate for banks to 0.8623 and 0.6696, respectively.

Kearifan Lokal Masyarakat Cibalong dalam Melestarikan Keanekaragaman dan Pola Bersarang Kelelawar Penghuni Gua di Kawasan Karst Cibalong Kabupaten Tasikmalaya Pada Pengembangan Model Pembelajaran Berbasis Kearifan Lokal di SD

2016 ◽  
Vol 1 (1) ◽  
pp. 19-29
Author(s):  
Mohammad Fahmi Nugraha
Keyword(s):  
Environmental Problems ◽  
Learning Model ◽  
Scientific Thinking ◽  
Model Based

The environmental problems at this time, especially the diversity of bat cave dwellers in the karst of Cibalong, Tasikmalaya should be given the special attention by all of the society elements, especially by the educators who must act real and solve the problems to give the view of knowledge to the community and the students in understanding the importance of bats which is considered as a pest and it is associated with mystical things. One of the effort is looking for and implementing  some of learning model based on the local wisdom to change and establish the scientific thinking of the sociaety and the students to analyze the presence of bat in term of the survival of the ecosystem. It is expected that bats and their habitats in Karst of Cibalong, Tasikmalaya can be preserved.

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