विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| मल्टीडायमेंशनल स्केलिंग (MDS)× | विवेचक विश्लेषण× | |
|---|---|---|
| क्षेत्र | सांख्यिकी | सांख्यिकी |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1952–1964 | 1936 |
| प्रवर्तक≠ | Warren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964) | Ronald A. Fisher |
| प्रकार≠ | Dimensionality reduction / visualization | Supervised classification and dimension reduction |
| मौलिक स्रोत≠ | Kruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29(1), 1–27. DOI ↗ | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗ |
| उपनाम | MDS, metric MDS, non-metric MDS, proximity scaling | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis |
| संबंधित≠ | 5 | 4 |
| सारांश≠ | Multidimensional scaling maps objects described only by pairwise similarities or dissimilarities into a low-dimensional geometric space so that distances in that space reflect the original proximity structure as faithfully as possible. It is widely used to visualize the hidden structure of psychological, social, and behavioral 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. |
| ScholarGateडेटासेट ↗ |
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