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  2. Range minimum query - Wikipedia

    en.wikipedia.org/wiki/Range_minimum_query

    However, the array will store pre-computed range minimum queries not for every range [i, j], but only for ranges whose size is a power of two. There are O(log n) such queries for each start position i, so the size of the dynamic programming table B is O(n log n). The value of B[i, j] is the index of the minimum of the range A[i…i+2 j-1].

  3. Range query (computer science) - Wikipedia

    en.wikipedia.org/wiki/Range_query_(computer_science)

    Given a function that accepts an array, a range query (,) on an array = [,..,] takes two indices and and returns the result of when applied to the subarray [, …,].For example, for a function that returns the sum of all values in an array, the range query ⁡ (,) returns the sum of all values in the range [,].

  4. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.

  5. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Associative array (or dictionary) of key and value pairs; can contain mixed types (keys and values), keys must be a hashable type {'key1': 1.0, 3: False} {} types.EllipsisType: immutable An ellipsis placeholder to be used as an index in NumPy arrays ... Ellipsis: float: immutable Double-precision floating-point number.

  6. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Pandas also supports the syntax data.iloc[n], which always takes an integer n and returns the nth value, counting from 0. This allows a user to act as though the index is an array-like sequence of integers, regardless of how it's actually defined. [9]: 110–113 Pandas supports hierarchical indices with multiple values per data point.

  7. Likelihood function - Wikipedia

    en.wikipedia.org/wiki/Likelihood_function

    The art of choosing the fixed log-likelihood difference is to make the confidence acceptably high while keeping the region acceptably small (narrow range of estimates). As more data are observed, instead of being used to make independent estimates, they can be combined with the previous samples to make a single combined sample, and that large ...

  8. Binary search - Wikipedia

    en.wikipedia.org/wiki/Binary_search

    Binary search Visualization of the binary search algorithm where 7 is the target value Class Search algorithm Data structure Array Worst-case performance O (log n) Best-case performance O (1) Average performance O (log n) Worst-case space complexity O (1) Optimal Yes In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search ...

  9. Resampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Resampling_(statistics)

    The best example of the plug-in principle, the bootstrapping method. Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio ...