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The mode of a sample is the element that occurs most often in the collection. For example, the mode of the sample [1, 3, 6, 6, 6, 6, 7, 7, 12, 12, 17] is 6. Given the list of data [1, 1, 2, 4, 4] its mode is not unique. A dataset, in such a case, is said to be bimodal, while a set with more than two modes may be described as multimodal.
The mode of the block can be retrieved from . By Theorem 1, the mode can be either an element of the prefix (indices of [:] before the start of the span), an element of the suffix (indices of [:] after the end of the span), or .
The normal way of entering quotation marks in text mode (two back ticks for the left and two apostrophes for the right), such as \text {a ``quoted'' word} will not work correctly. As a workaround, you can use the Unicode left and right quotation mark characters, which are available from the "Symbols" dropdown panel beneath the editor: \text { a ...
– Technologies, related to the Internet, have large distribution and formulas, represented on their base, do not require additional software. It befits for such genre of sites a
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
In Python 3.x the range() function [28] returns a generator which computes elements of the list on demand. Elements are only generated when they are needed (e.g., when print(r[3]) is evaluated in the following example), so this is an example of lazy or deferred evaluation:
The following Windows C++ code is an example of a Category 1 leap year bug. It will work properly until the current date becomes February 29 of a leap year. Then, it will modify st to represent February 29 of a common year, a date which does not actually exist. Passing st to any function that accepts a SYSTEMTIME struct as a parameter will ...
Mean shift is a procedure for locating the maxima—the modes—of a density function given discrete data sampled from that function. [1] This is an iterative method, and we start with an initial estimate . Let a kernel function be given. This function determines the weight of nearby points for re-estimation of the mean.