تقرير
Metric distances derived from cosine similarity and Pearson and Spearman correlations
العنوان: | Metric distances derived from cosine similarity and Pearson and Spearman correlations |
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المؤلفون: | van Dongen, Stijn, Enright, Anton J. |
سنة النشر: | 2012 |
المجموعة: | Computer Science Statistics |
مصطلحات موضوعية: | Statistics - Methodology, Computer Science - Learning |
الوصف: | We investigate two classes of transformations of cosine similarity and Pearson and Spearman correlations into metric distances, utilising the simple tool of metric-preserving functions. The first class puts anti-correlated objects maximally far apart. Previously known transforms fall within this class. The second class collates correlated and anti-correlated objects. An example of such a transformation that yields a metric distance is the sine function when applied to centered data. Comment: 5 pages, 1 figure |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/1208.3145 |
رقم الأكسشن: | edsarx.1208.3145 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |