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The Soundex code for a name consists of a letter followed by three numerical digits: the letter is the first letter of the name, and the digits encode the remaining consonants. Consonants at a similar place of articulation share the same digit so, for example, the labial consonants B, F, P, and V are each encoded as the number 1.
Daitch–Mokotoff Soundex (D–M Soundex) is a phonetic algorithm invented in 1985 by Jewish genealogists Gary Mokotoff and Randy Daitch.It is a refinement of the Russell and American Soundex algorithms designed to allow greater accuracy in matching of Slavic and Yiddish surnames with similar pronunciation but differences in spelling.
Soundex, which was developed to encode surnames for use in censuses. Soundex codes are four-character strings composed of a single letter followed by three numbers. Daitch–Mokotoff Soundex, which is a refinement of Soundex designed to better match surnames of Slavic and Germanic origin. Daitch–Mokotoff Soundex codes are strings composed of ...
Metaphone is a phonetic algorithm, published by Lawrence Philips in 1990, for indexing words by their English pronunciation. [1] It fundamentally improves on the Soundex algorithm by using information about variations and inconsistencies in English spelling and pronunciation to produce a more accurate encoding, which does a better job of matching words and names which sound similar.
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that at most one subcomponent is Gaussian and that the subcomponents are statistically independent from each other. [1]