Abstract
This paper considers the issues involved in developing a generic problem solver to be used within a grid environment for the monitoring and control of instrumentation. The specific feature of such an environment is that the type of data to be processed, as well as the problem, is not always known in advance. Therefore, it is necessary to develop a problem solver architecture that addresses this issue. We propose to analyze the performance of the problem solving algorithms available within the WEKA toolkit and determine a decision tree of the best performing algorithm for a given type of data. For this purpose the algorithms have been tested using 51 datasets either drawn from publicly available repositories or generated in a grid-enabled environment
| Original language | English |
|---|---|
| Pages | 287-292 |
| DOIs | |
| Publication status | Published - 2006 |
| Externally published | Yes |
Keywords
- Data Mining
- Algorithm
- Problem solving