পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| কোরস্পন্ডেন্স অ্যানালাইসিস× | মাল্টিডাইমেনশনাল স্কেলিং (MDS)× | |
|---|---|---|
| ক্ষেত্র | পরিসংখ্যান | পরিসংখ্যান |
| পরিবার | Latent structure | Latent structure |
| উদ্ভবের বছর≠ | 1984 | 1952–1964 |
| প্রবর্তক≠ | Jean-Paul Benzécri; Michael Greenacre | Warren S. Torgerson (metric MDS, 1952); Joseph B. Kruskal (non-metric MDS, 1964) |
| ধরন≠ | Exploratory multivariate technique for categorical data | Dimensionality reduction / visualization |
| মৌলিক উৎস≠ | Greenacre, M. J. (1984). Theory and Applications of Correspondence Analysis. Academic Press. ISBN: 978-0-12-299050-2 | Kruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29(1), 1–27. DOI ↗ |
| অপর নাম | CA, Simple Correspondence Analysis, Reciprocal Averaging, Karşılıklı Uyum Analizi | MDS, metric MDS, non-metric MDS, proximity scaling |
| সম্পর্কিত≠ | 2 | 5 |
| সারসংক্ষেপ≠ | Correspondence Analysis (CA) is an exploratory multivariate technique for visualizing the association structure of a two-way contingency table. Developed systematically by Jean-Paul Benzécri in France during the 1960s–1970s and brought to an English-language audience by Michael Greenacre in 1984, CA decomposes the chi-square statistic of a cross-tabulation to produce a low-dimensional joint display — called a biplot — in which rows and columns are represented as points whose proximities reflect their associations. | 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. |
| ScholarGateডেটাসেট ↗ |
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