The primary goal of Brea is to serve as an algorithm catalog to allow the usage of abstract currently best fitting (CBF) algorithms, as required by the Cloud-Assisted Meta Programming (CAMP) paradigm. Thereby Brea is required to host and deliver algorithms as well as to cyclically evaluate and index them with respect to their corresponding metrics, using Rian. An example for such a metric would be the average prediction accuracy within a fixed set of gold standard samples of the respective domain of application (e.g. latin handwriting samples, spoken word samples, TCGA gene expression data, etc.). Consequently Brea is also required to host or connect these samples by using Deet.
Due to this approach Brea allows the implementation of smart analytics projects, that are automatically kept up-to-date by a minimum of maintenance costs. Also Brea supports scientific applications, by facilitating a local (workgroup, lab, institution) or global publication, application and evaluation of algorithms.
Installation using PIP
$ pip install brea
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