Original Contribution: Stacked generalization
Neural Networks
Combining the results of several neural network classifiers
Neural Networks
A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal combinations of pattern classifiers
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data mining models as services on the internet
ACM SIGKDD Explorations Newsletter
An Architecture to Support Distributed Data Mining Services in E-Commerce Environments
WECWIS '00 Proceedings of the Second International Workshop on Advance Issues of E-Commerce and Web-Based Information Systems (WECWIS 2000)
Hi-index | 12.05 |
This paper describes CSF/DC, a Web-based system for classifier sharing and fusion. CSF/DC enables the sharing of classification models, by allowing the upload and download of such models expressed in the industry standard PMML language on the system's online classifier repository. CSF/DC also leverages the individual knowledge shared by such (potentially heterogeneous) classification models and offers quality decision support to any user with an Internet connection through a guided procedure. However, some organizations or individuals might want to share the predictive capabilities of their classification models without compromising their internal structure. This is accommodated by CSF/DC through the use of Web services. Specifically, CSF/DC allows the participation of classifier Web services in the decision fusion process, by offering the necessary online mechanisms for the registration and invocation of such Web services developed and installed at remote sites.