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This section gives examples of diagnostics generated by the markup validation service, and suggests possible fixes. Diagnostics are by line and column of the generated HTML for the page. It may be helpful to obtain the HTML in order to understand the diagnostic. For example, if you using the Firefox browser, you can type control-U to see the HTML.
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]
A validator is a computer program used to check the validity or syntactical correctness of a fragment of code or document. The term is commonly used in the context of validating HTML, [1] [2] CSS, and XML documents like RSS feeds, though it can be used for any defined format or language.
In the context of hardware and software systems, formal verification is the act of proving or disproving the correctness of a system with respect to a certain formal specification or property, using formal methods of mathematics. [1] Formal verification is a key incentive for formal specification of systems, and is at the core of formal methods.
Hypertext Markup Language (HTML) is the standard markup language [a] for documents designed to be displayed in a web browser. It defines the content and structure of web content. It is often assisted by technologies such as Cascading Style Sheets (CSS) and scripting languages such as JavaScript, a programming language.
The Markup Validation Service is a validator by the World Wide Web Consortium (W3C) that allows Internet users to check pre-HTML5 HTML and XHTML documents for well-formed markup against a document type definition (DTD). Markup validation is an important step towards ensuring the technical quality of web pages.
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]
Verification is intended to check that a product, service, or system meets a set of design specifications. [6] [7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results.