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  2. Weyburn-Midale Carbon Dioxide Project - Wikipedia

    en.wikipedia.org/wiki/Weyburn-Midale_Carbon...

    The results form the most complete, comprehensive, peer-reviewed data set in the world for CO 2 geological storage. However, additional research was deemed to be needed to further develop and refine CO 2 monitoring and verification technologies. With this in mind, a second and final phase of research was developed and began in the year 2005 ...

  3. The Pile (dataset) - Wikipedia

    en.wikipedia.org/wiki/The_Pile_(dataset)

    [1] [5] Compared to other datasets, the Pile's main distinguishing features are that it is a curated selection of data chosen by researchers at EleutherAI to contain information they thought language models should learn and that it is the only such dataset that is thoroughly documented by the researchers who developed it.

  4. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Data from nine subjects collected using P300-based brain-computer interface for disabled subjects. Split into four sessions for each subject. MATLAB code given. 1,224 Text Classification 2008 [263] [264] U. Hoffman et al. Heart Disease Data Set Attributed of patients with and without heart disease.

  5. Self-Monitoring, Analysis and Reporting Technology - Wikipedia

    en.wikipedia.org/wiki/Self-Monitoring,_Analysis...

    Self-Monitoring, Analysis, and Reporting Technology (S.M.A.R.T. or SMART) is a monitoring system included in computer hard disk drives (HDDs) and solid-state drives (SSDs). [3] Its primary function is to detect and report various indicators of drive reliability, or how long a drive can function while anticipating imminent hardware failures.

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    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]

  7. Key-sequenced data set - Wikipedia

    en.wikipedia.org/wiki/Key-sequenced_data_set

    A key-sequenced data set (KSDS) is a type of data set used by IBM's VSAM computer data storage system. [ 1 ] : 5 Each record in a KSDS data file is embedded with a unique key. [ 1 ] : 20 A KSDS consists of two parts, the data component and a separate index file known as the index component which allows the system to physically locate the record ...

  8. Refinement (computing) - Wikipedia

    en.wikipedia.org/wiki/Refinement_(computing)

    Data refinement is used to convert an abstract data model (in terms of sets for example) into implementable data structures (such as arrays). [ citation needed ] Operation refinement converts a specification of an operation on a system into an implementable program (e.g., a procedure ).

  9. Storage Management Initiative – Specification - Wikipedia

    en.wikipedia.org/wiki/Storage_Management...

    The Storage Management Initiative Specification, commonly called SMI-S, is a computer data storage management standard developed and maintained by the Storage Networking Industry Association (SNIA). It has also been ratified as an ISO standard. [ 1 ]