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  2. Data binning - Wikipedia

    en.wikipedia.org/wiki/Data_binning

    Data binning, also called data discrete binning or data bucketing, is a data pre-processing technique used to reduce the effects of minor observation errors. The original data values which fall into a given small interval, a bin , are replaced by a value representative of that interval, often a central value ( mean or median ).

  3. Bootstrap aggregating - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_aggregating

    As most tree based algorithms use linear splits, using an ensemble of a set of trees works better than using a single tree on data that has nonlinear properties (i.e. most real world distributions). Working well with non-linear data is a huge advantage because other data mining techniques such as single decision trees do not handle this as well.

  4. Binning (metagenomics) - Wikipedia

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

    In metagenomics, binning is the process of grouping reads or contigs and assigning them to individual genome. Binning methods can be based on either compositional features or alignment (similarity), or both.

  5. Grouped data - Wikipedia

    en.wikipedia.org/wiki/Grouped_data

    Another method of grouping the data is to use some qualitative characteristics instead of numerical intervals. For example, suppose in the above example, there are three types of students: 1) Below normal, if the response time is 5 to 14 seconds, 2) normal if it is between 15 and 24 seconds, and 3) above normal if it is 25 seconds or more, then the grouped data looks like:

  6. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    An example of data mining related to an integrated-circuit (IC) production line is described in the paper "Mining IC Test Data to Optimize VLSI Testing." [12] In this paper, the application of data mining and decision analysis to the problem of die-level functional testing is described. Experiments mentioned demonstrate the ability to apply a ...

  7. Biomedical data science - Wikipedia

    en.wikipedia.org/wiki/Biomedical_data_science

    Biomedical data science is a multidisciplinary field which leverages large volumes of data to promote biomedical innovation and discovery. Biomedical data science draws from various fields including Biostatistics , Biomedical informatics , and machine learning , with the goal of understanding biological and medical data.

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    mail.aol.com/?icid=aol.com-nav

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  9. Flow cytometry bioinformatics - Wikipedia

    en.wikipedia.org/wiki/Flow_cytometry_bioinformatics

    An example of frequency difference gating, created using the flowFP Bioconductor package. The dots represent individual events in an FCS file. The rectangles represent the bins. Probability binning is a non-gating analysis method in which flow cytometry data is split into quantiles on a univariate basis. [51]