| Poll |
Data mining/analytic techniques you use frequently: [784 votes total]
|
| Decision Trees/Rules (107) |  14% |
| Clustering (101) |  13% |
| Regression (90) |  11% |
| Statistics (80) |  10% |
| Visualization (63) |  8% |
| Neural Nets (61) |  8% |
| Association rules (54) |  7% |
| Nearest Neighbor (34) |  4% |
| SVM (Support vector machine) (31) |  4% |
| Bayesian (30) |  4% |
| Sequence/Time series analysis (26) |  3% |
| Boosting (25) |  3% |
| Hybrid methods (23) |  3% |
| Bagging (20) |  3% |
| Genetic algorithms (19) |  2% |
| Other (20) |  3% | |
Comments
Ralf Klinkenberg, Concept drift detection & handling, topic tracking
Regurlarly used other data mining methods:
- methods for concept drift detection and handling
(in classification tasks using Support Vector Machines),
e.g. concept/topic tracking
- methods for chance detection
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