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Snippets about coefficient

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Pearson Coefficient

In statistics, the Pearson product-moment correlation coefficient (sometimes referred to as the PMCC, and typically denoted by r) is a measure of the correlation (linear dependence) between two variables X and Y, giving a value between +1 and −1 inclusive. It is widely used in the sciences as a measure of the strength of linear dependence between two variables. It was first introduced by Francis Galton in the 1880s, and is named after Karl Pearson. The correlation coefficient is sometimes called "Pearson's r."

Python / Pearson, coefficient, correlation / by ThePeppersStudio (437 days, 9.45 hours ago)

Euclidean Coefficient

Python / Euclidean, coefficient, correlation / by ThePeppersStudio (438 days, 10.74 hours ago)

Tanamoto Coefficient

The Pearson correlation works well for the blog dataset where the values are actual word counts. However, this dataset just has 1s and 0s for presence or absence, and it would be more useful to define some measure of overlap between the people who want two items. For this, there is a measure called the Tanimoto coefficient, which is the ratio of the intersection set (only the items that are in both sets) to the union set (all the items in either set). This will return a value between 1.0 and 0.0. A value of 1.0 indicates that nobody who wants the first item wants the second one, and 0.0 means that exactly the same set of people want the two items.

Python / Tanimoto, coefficient, correlation / by ThePeppersStudio (441 days, 13.99 hours ago)