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The frequency of data loss and the impact can be greatly mitigated by taking proper precautions, those of which necessary can vary depending on the type of data loss. For example, multiple power circuits with battery backup and a generator only protect against power failures, though using an Uninterruptible Power Supply can protect drive ...
In statistics, typically a loss function is used for parameter estimation, and the event in question is some function of the difference between estimated and true values for an instance of data. The concept, as old as Laplace, was reintroduced in statistics by Abraham Wald in the middle of the 20th century. [ 2]
The Huber loss function describes the penalty incurred by an estimation procedure f. Huber (1964) defines the loss function piecewise by [1] This function is quadratic for small values of a, and linear for large values, with equal values and slopes of the different sections at the two points where . The variable a often refers to the residuals ...
Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. . The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data or produce summary data and statistics at different aggregation levels for various applications
In statistics, the residual sum of squares ( RSS ), also known as the sum of squared residuals ( SSR) or the sum of squared estimate of errors ( SSE ), is the sum of the squares of residuals (deviations predicted from actual empirical values of data). It is a measure of the discrepancy between the data and an estimation model, such as a linear ...
In mathematics, statistics, finance, [ 1] and computer science, particularly in machine learning and inverse problems, regularization is a process that changes the result answer to be "simpler". It is often used to obtain results for ill-posed problems or to prevent overfitting. [ 2]
Data compression. In information theory, data compression, source coding, [ 1] or bit-rate reduction is the process of encoding information using fewer bits than the original representation. [ 2] Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy.
Data loss prevention (DLP) software detects potential data breaches/data exfiltration transmissions and prevents them by monitoring, [1] detecting and blocking sensitive data while in use (endpoint actions), in motion (network traffic), and at rest (data storage). [2] The terms "data loss" and "data leak" are related and are often used ...