Reservoir Sampling - Sampling from a stream of elements
Oct 8, 2007 If you don't find programming algorithms interesting, this post is not for you. Problem Statement Reservoir Sampling is an algorithm for sampling elements from a stream of data. Imagine you are given a really large stream of data elements, for example: Queries on google searches in May Products bought at Walmart during the Christmas season Names in a phone book Your goal is to efficien
Repeatable sampling of data sets in BigQuery for machine learning
Repeatable sampling of data sets in BigQuery for machine learning An efficient, fast, and repeatable selection method that works on very large data sets. Doing machine learning on distributed data sets is methodologically similar to working with data that fits in-memory—train your algorithm on a subset of the data, validate on another subset, and finally test with a different subset. In this post,
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BigQuery でランダムサンプリング - Qiita
