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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2074/1932
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Full metadata record
| DC Field | Value | Language |
|---|
| contributor.author | Gupta, S K | - |
| contributor.author | Somayajulu, D V L N | - |
| contributor.author | Arora, J K | - |
| contributor.author | Vasudha, B | - |
| date.accessioned | 2006-07-03T04:51:20Z | - |
| date.available | 2006-07-03T04:51:20Z | - |
| date.issued | 1998 | - |
| identifier.citation | Database and Expert Systems Applications, Proceedings Ninth International Workshop on, 246 - 251p. | en |
| identifier.uri | http://eprint.iitd.ac.in/dspace/handle/2074/1932 | - |
| description.abstract | The paper presents an algorithm to solve the problem of classification for data mining applications. This is a decision tree classifier which uses modified gini index as the partitioning criteria. A pre-sorting technique is used to overcome the problem of sorting at each node of the tree. This technique is integrated with a breadth first tree growth strategy which enables us to calculate the best partition for each of the leaf nodes in a single scan of a database. We have implemented this algorithm using depth first tree growth strategy also. The algorithm uses a dynamic pruning approach which reduces the number of scans of the database and does away with a separate tree pruning phase. The proof of correctness, analysis and performance study are also presented | en |
| format.extent | 64569 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | en |
| subject | data mining applications | en |
| subject | dynamic pruning | en |
| title | Scalable classifiers with dynamic pruning | en |
| type | Article | en |
| Appears in Collections: | Computer Science and Engineering
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Files in This Item:
| File |
Description |
Size | Format |
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| guptasca1998.pdf | | 63Kb | Adobe PDF | View/Open |
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