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Relative change. In any quantitative science, the terms relative change and relative difference are used to compare two quantities while taking into account the "sizes" of the things being compared, i.e. dividing by a standard or reference or starting value. [1] The comparison is expressed as a ratio and is a unitless number.
Fold change. Fold change is a measure describing how much a quantity changes between an original and a subsequent measurement. It is defined as the ratio between the two quantities; for quantities A and B the fold change of B with respect to A is B / A. In other words, a change from 30 to 60 is defined as a fold-change of 2.
In mathematics, a percentage (from Latin per centum 'by a hundred') is a number or ratio expressed as a fraction of 100. It is often denoted using the percent sign (%), [1] although the abbreviations pct., pct, and sometimes pc are also used. [2] A percentage is a dimensionless number (pure number), primarily used for expressing proportions ...
Precision and recall. Precision and recall. In pattern recognition, information retrieval, object detection and classification (machine learning), precision and recall are performance metrics that apply to data retrieved from a collection, corpus or sample space . Precision (also called positive predictive value) is the fraction of relevant ...
Color difference. In color science, color difference or color distance is the separation between two colors. This metric allows quantified examination of a notion that formerly could only be described with adjectives. Quantification of these properties is of great importance to those whose work is color-critical.
Magnetic declination (also called magnetic variation) is the angle between magnetic north and true north at a particular location on the Earth's surface. The angle can change over time due to polar wandering . Magnetic north is the direction that the north end of a magnetized compass needle points, which corresponds to the direction of the ...
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Numerical differentiation. Finite difference estimation of derivative. In numerical analysis, numerical differentiation algorithms estimate the derivative of a mathematical function or function subroutine using values of the function and perhaps other knowledge about the function.