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Functions involving two or more variables require multidimensional array indexing techniques. The latter case may thus employ a two-dimensional array of power[x][y] to replace a function to calculate x y for a limited range of x and y values. Functions that have more than one result may be implemented with lookup tables that are arrays of ...
The index is known by several other names, especially Sørensen–Dice index, [3] Sørensen index and Dice's coefficient. Other variations include the "similarity coefficient" or "index", such as Dice similarity coefficient ( DSC ).
In information retrieval, Okapi BM25 (BM is an abbreviation of best matching) is a ranking function used by search engines to estimate the relevance of documents to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson , Karen Spärck Jones , and others.
In probability theory and statistics, the index of dispersion, [1] dispersion index, coefficient of dispersion, relative variance, or variance-to-mean ratio (VMR), like the coefficient of variation, is a normalized measure of the dispersion of a probability distribution: it is a measure used to quantify whether a set of observed occurrences are clustered or dispersed compared to a standard ...
This index uses the arithmetic average of the current and based period quantities for weighting. It is considered a pseudo-superlative formula and is symmetric. [12] The use of the Marshall-Edgeworth index can be problematic in cases such as a comparison of the price level of a large country to a small one.
The Wilcoxon signed-rank test is a non-parametric rank test for statistical hypothesis testing used either to test the location of a population based on a sample of data, or to compare the locations of two populations using two matched samples. [1]
The Nash–Sutcliffe coefficient masks important behaviors that if re-cast can aid in the interpretation of the different sources of model behavior in terms of bias, random, and other components. [11]
As changes, the weighting function () emphasizes different parts of the input function (); If is a positive value, then () is equal to () that slides or is shifted along the -axis toward the right (toward +) by the amount of , while if is a negative value, then () is equal to () that slides or is shifted toward the left (toward ) by the amount ...