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  2. 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]

  3. Spring Boot - Wikipedia

    en.wikipedia.org/wiki/Spring_Boot

    Spring Boot is a convention-over-configuration extension for the Spring Java platform intended to help minimize configuration concerns while creating Spring-based applications. [ 4 ] [ 5 ] The application can still be adjusted for specific needs, but the initial Spring Boot project provides a preconfigured "opinionated view" of the best ...

  4. Data validation - Wikipedia

    en.wikipedia.org/wiki/Data_validation

    Data type validation is customarily carried out on one or more simple data fields. The simplest kind of data type validation verifies that the individual characters provided through user input are consistent with the expected characters of one or more known primitive data types as defined in a programming language or data storage and retrieval ...

  5. Data verification - Wikipedia

    en.wikipedia.org/wiki/Data_verification

    Data verification helps to determine whether data was accurately translated when data is transferred from one source to another, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneous data loss .

  6. Backup validation - Wikipedia

    en.wikipedia.org/wiki/Backup_validation

    Backup validation is the process whereby owners of computer data may examine how their data was backed up in order to understand what their risk of data loss might be. It also speaks to optimization of such processes, charging for them as well as estimating future requirements, sometimes called capacity planning.

  7. Spring Roo - Wikipedia

    en.wikipedia.org/wiki/Spring_Roo

    Spring Boot (version 1.4 or above) Spring Data JPA (version 1.10 or above) Spring Framework (version 4 or above) Spring Security (version 4 or above) Spring Web Flow (installation and flow definition) SpringSource Tool Suite (STS has an embedded Roo shell and Roo command helpers) Thymeleaf (version 3 or above)

  8. Jakarta Persistence - Wikipedia

    en.wikipedia.org/wiki/Jakarta_Persistence

    The Spring Data JPA is an implementation of the repository abstraction that is a key building block of domain-driven design based on the Java application framework Spring. It transparently supports all available JPA implementations and supports CRUD operations as well as the convenient execution of database queries.

  9. JHipster - Wikipedia

    en.wikipedia.org/wiki/JHipster

    JHipster provides tools to generate a project with a Java stack on the server side (using Spring Boot) and a responsive Web front-end on the client side (with Angular/React and Bootstrap). It can also create microservice stack with support for Netflix OSS, Docker and Kubernetes.