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Note that you may also specify the § height of individual rows, and if they add up to more than the table height you specified or if word wrapping increases row height, the table height you specified will be ignored and the table height increased as needed to accommodate all the rows (except on mobile where the bottom of the table will be cut ...
As defined in set theory, the maximum and minimum of a set are the greatest and least elements in the set, respectively. Unbounded infinite sets, such as the set of real numbers, have no minimum or maximum. In statistics, the corresponding concept is the sample maximum and minimum.
The minimum and the maximum value are the first and last order statistics (often denoted X (1) and X (n) respectively, for a sample size of n). If the sample has outliers, they necessarily include the sample maximum or sample minimum, or both, depending on whether they are extremely high or low. However, the sample maximum and minimum need not ...
For that reason, many images beside an infobox are typically set as "left|" to align along the left-margin, rather than floated into the center of the page. Note the order of precedence from the right margin: first, come infoboxes or images using "right|", then come the floating-tables, and lastly, any text will wrap that can still fit. If the ...
The maximum of a subset of a preordered set is an element of which is greater than or equal to any other element of , and the minimum of is again defined dually. In the particular case of a partially ordered set , while there can be at most one maximum and at most one minimum there may be multiple maximal or minimal elements.
The height of the bar represents the number of observations (years) with a return % in the range represented by the respective bin. A scatterplot showing negative correlation between two variables: Scatter plot (dot plot) x position; y position; symbol/glyph; color; size; Uses Cartesian coordinates to display values for typically two variables ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Note how the use of A[i][j] with multi-step indexing as in C, as opposed to a neutral notation like A(i,j) as in Fortran, almost inevitably implies row-major order for syntactic reasons, so to speak, because it can be rewritten as (A[i])[j], and the A[i] row part can even be assigned to an intermediate variable that is then indexed in a separate expression.