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  2. Learning classifier system - Wikipedia

    en.wikipedia.org/wiki/Learning_classifier_system

    A step-wise schematic illustrating a generic Michigan-style learning classifier system learning cycle performing supervised learning. Keeping in mind that LCS is a paradigm for genetic-based machine learning rather than a specific method, the following outlines key elements of a generic, modern (i.e. post-XCS) LCS algorithm.

  3. DECIPHER (software) - Wikipedia

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

    Print/export Download as PDF; Printable version; In other projects ... DECIPHER is a software that can be used to decipher and manage biological sequences efficiently ...

  4. Machine learning in bioinformatics - Wikipedia

    en.wikipedia.org/wiki/Machine_learning_in...

    Many algorithms were developed to classify microbial communities according to the health condition of the host, regardless of the type of sequence data, e.g. 16S rRNA or whole-genome sequencing (WGS), using methods such as least absolute shrinkage and selection operator classifier, random forest, supervised classification model, and gradient ...

  5. DECIPHER - Wikipedia

    en.wikipedia.org/wiki/DECIPHER

    DECIPHER is a web-based resource and database of genomic variation data from analysis of patient DNA. [ 1 ] [ 2 ] [ 3 ] It documents submicroscopic chromosome abnormalities ( microdeletions and duplications ) and pathogenic sequence variants (single nucleotide variants - SNVs, Insertions, Deletions, InDels), from over 25000 patients and maps ...

  6. Genetic fuzzy systems - Wikipedia

    en.wikipedia.org/wiki/Genetic_fuzzy_systems

    Much work has been done to develop or adapt methodologies that are capable of automatically identifying a fuzzy system from numerical data. Particularly in the framework of soft computing, significant methodologies have been proposed with the objective of building fuzzy systems by means of genetic algorithms (GAs) or genetic programming (GP).

  7. Holland's schema theorem - Wikipedia

    en.wikipedia.org/wiki/Holland's_schema_theorem

    Holland's schema theorem, also called the fundamental theorem of genetic algorithms, [1] is an inequality that results from coarse-graining an equation for evolutionary dynamics. The Schema Theorem says that short, low-order schemata with above-average fitness increase exponentially in frequency in successive generations.

  8. Binning (metagenomics) - Wikipedia

    en.wikipedia.org/wiki/Binning_(Metagenomics)

    PCAHIER, [17] another binning algorithm developed by the Georgia Institute of Technology., employs n-mer oligonucleotide frequencies as the features and adopts a hierarchical classifier (PCAHIER) for binning short metagenomic fragments. The principal component analysis was used to reduce the high dimensionality of the feature space.

  9. John Henry Holland - Wikipedia

    en.wikipedia.org/wiki/John_Henry_Holland

    John Henry Holland was born on February 2, 1929 in Fort Wayne, Indiana, the elder child of [3] son of Gustave A. Holland (b. July 24, 1896, Russian Poland) and Mildred P. Gfroerer (b.