Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Кластерний аналіз× | Дискримінантний аналіз× | |
|---|---|---|
| Галузь | Статистика | Статистика |
| Родина | Latent structure | Latent structure |
| Рік появи≠ | 1939–1967 | 1936 |
| Автор методу≠ | Robert C. Tryon (early development); Ward (1963) for hierarchical; MacQueen (1967) for k-means | Ronald A. Fisher |
| Тип≠ | Unsupervised classification / grouping | Supervised classification and dimension reduction |
| Основоположне джерело≠ | Everitt, B. S., Landau, S., Leese, M. & Stahl, D. (2011). Cluster Analysis (5th ed.). Wiley. ISBN: 978-0470749913 | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗ |
| Інші назви | clustering, unsupervised classification, data clustering, numerical taxonomy | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis |
| Пов'язані≠ | 5 | 4 |
| Підсумок≠ | Cluster analysis is a family of unsupervised multivariate techniques that partition a set of objects or observations into internally homogeneous, mutually distinct groups — clusters — based on measured characteristics, without any prior knowledge of group membership. It is widely used in market segmentation, bioinformatics, psychology, and social science to reveal natural groupings in data. | Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error. |
| ScholarGateНабір даних ↗ |
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