A hybrid approach of neural network and memory-based learning to data mining

By Chung K. Shin, Ui Tak Yun, Huy Kang Kim, Sang-Chan Park. 2000

89 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Eoin M. Kenny
2. Mark T. Keane
3. Debashree Devi
4. Saroj Kumar Biswas
5. Akhil Kr. Das
6. Biswajit Purkayastha
7. Heisnam Rohen Singh
8. Manomita Chakraborty

In Computational Theory and Mathematics

1. Tong Wang
2. Eoin M. Kenny
3. Mark T. Keane
4. Kwang Hyuk Im
5. Sankar Kumar Pal
6. Hassan Rafique
7. Qihang Lin
8. Sang-Chan Park

Citations in the corpus

• Hybrid Decision Making: When Interpretable Models Collaborate With Black-Box Models (2018, background): “One of the earliest works [15] proposed NBTree which induces a hybrid of decision-tree classi€ers and Naive-Bayes classi€ers, [29] proposed a system combining neural network and memory-based learning, [12] combined SVM and logistic regression to forecast intermiŠent demand of spare parts, etc.”
• Data mining in soft computing framework: a survey (2002, background): “Some recent work in this direction are available in Ref. [83], [84], [ 85 ], [86].”
• Case-based reasoning and neural network based expert system for personalization (2007, methodology): “with Applications a hybrid approach of neural network (NN) and CBR named as MANN (memory and neural network based learning) ( Shin, Yun, Kim, & Park, 2000 ).”
• Model-Agnostic Linear Competitors - When Interpretable Models Compete and Collaborate with Black-Box Models (2019, methodology): “For example, (Kohavi 1996) combined a decision tree with a Naive Bayes model, (Shin et al. 2000) proposed a system combining neural network and memory-based learning, (Hua and Zhang 2006) combined SVM and logistic regression, etc.”
• How Case-Based Reasoning Explains Neural Networks: A Theoretical Analysis of XAI Using Post-Hoc Explanation-by-Example from a Survey of ANN-CBR Twin-Systems (2019, methodology): “Shin and colleagues [46, 47] proposed that the sensitivity and activity measures seemed to perform best, (though conclusions are different for different datasets) arguing that their fidelity to the function being computed by the MLP was better.”
• Hybrid case-based reasoning system by cost-sensitive neural network for classification (2016, methodology): “Sensitivity, activity saliency and relevance mechanisms are used in Shin and Park (1999), Shin et al. (2000), Im and Park (2007) and Park et al. (2004) to find symbolic feature weights from back-propagation neural network (BPNN).”