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Most Ensembl Genomes data is stored in MySQL relational databases and can be accessed by the Ensembl REST interface, the Perl API, Biomart or online. [5] Ensembl Genomes is an open project, and most of the code, tools, and data are available to the public. [6] Ensembl and Ensembl Genomes software uses an Apache 2.0 license [7] license.
OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
Ensembl makes these data freely accessible to the world research community. All the data and code produced by the Ensembl project is available to download, [7] and there is also a publicly accessible database server allowing remote access. In addition, the Ensembl website provides computer-generated visual displays of much of the data.
[2] [59] Machine learning can be used for this knowledge extraction task using techniques such as natural language processing to extract the useful information from human-generated reports in a database. Text Nailing, an alternative approach to machine learning, capable of extracting features from clinical narrative notes was introduced in 2017.
Ensemble learning trains two or more machine learning algorithms on a specific classification or regression task. The algorithms within the ensemble model are generally referred as "base models", "base learners", or "weak learners" in literature.
Database of grayscale handwritten digits. 60,000 image, label classification 1994 [1] LeCun et al. Extended MNIST: Database of grayscale handwritten digits and letters. 810,000 image, label classification 2010 [2] NIST 80 Million Tiny Images: 80 million 32×32 images labelled with 75,062 non-abstract nouns. 80,000,000 image, label 2008 [3 ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Based at the EMBL-EBI, the Ensembl [11] is a database organized around genomic data, maintained by the Ensembl Project. Tasked with the continuous annotation of the genomes of model organisms, Ensembl provides researchers a comprehensive resource of relevant biological information about each specific genome. The annotation of the stored ...