Algorithms

Think Bayes

Bayesian Statistics Made Simple by Allen B. Downey Download Think Bayes in PDF . Read Think Bayes in HTML . Description

Bloom filter

A Bloom filter , conceived by Burton Howard Bloom in 1970, [ 1 ] is a space-efficient probabilistic data structure that is used to test whether an element is a member of a set . False positive retrieval results are possible, but false negatives are not; i.e. a query returns either "inside set (may be wrong)" or "definitely not in set". Elements can be added to the set, but not removed (though this can be addressed with a counting filter). The more elements that are added to the set, the larger the probability of false positives. [ edit ] Algorithm description An example of a Bloom filter, representing the set { x , y , z }.

How are bloom filters used in HBase

Fun - Educational

Hexagonal tiling

Text extraction

Natural language

Language

Selection algorithm

In computer science , a selection algorithm is an algorithm for finding the k th smallest number in a list (such a number is called the k th order statistic ). This includes the cases of finding the minimum , maximum , and median elements. There are , worst-case linear time, selection algorithms. Selection is a subproblem of more complex problems like the nearest neighbor problem and shortest path problems. [ edit ] Selection by sorting

Parallel

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