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What (who) is data validation - definition
Data validation
TECHNICAL PROCESS
Data Checking; Validation rule; Validation routine; Input validation; Validation scheme; Presence check; Data Validation; Cross-reference validation; Validation of data
In computer science, data validation is the process of ensuring data has undergone data cleansing to ensure they have data quality, that is, that they are both correct and useful. It uses routines, often called "validation rules", "validation constraints", or "check routines", that check for correctness, meaningfulness, and security of data that are input to the system.
Data validation and reconciliation
Random and systematic errors
Sensor and topological redundancy
Calculable and non-calculable systems
TECHNOLOGY TO CORRECT MEASUREMENTS IN INDUSTRIAL PROCESSES
User:Robcha/Data Validation and Reconciliation; Data Validation and Reconciliation; Data reconciliation; Industrial process data validation and reconciliation
Industrial process data validation and reconciliation, or more briefly, process data reconciliation (PDR), is a technology that uses process information and mathematical methods in order to automatically ensure data validation and reconciliation by correcting measurements in industrial processes. The use of PDR allows for extracting accurate and reliable information about the state of industry processes from raw measurement data and produces a single consistent set of data representing the most likely process operation.
Training, validation, and test data sets
THREE DATASETS USED IN MACHINE LEARNING
Training set; Validation set; Dataset (machine learning); Training data set; Training data; Test set; Training, test and validation sets; Training, test, and validation sets; Out-of-sample; Trainable parameter; Trained parameter; Train parameter; Model training; Training, validation, and test sets; Holdout data set; Training, validation, and test datasets; Training, validation, and test data; Training dataset
In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data.
