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Calculate the sum of squared deviations from the class means (SDCM). Choose a new way of dividing the data into classes, perhaps by moving one or more data points from one class to a different one. New class deviations are then calculated, and the process is repeated until the sum of the within class deviations reaches a minimal value.
In statistics, the intraclass correlation, or the intraclass correlation coefficient (ICC), [1] is a descriptive statistic that can be used when quantitative measurements are made on units that are organized into groups. It describes how strongly units in the same group resemble each other.
Along the horizontal axis, the limits of the class intervals for an ogive are marked. Based on the limit values, points above each are placed with heights equal to either the absolute or relative cumulative frequency. The shape of an ogive is obtained by connecting each of the points to its neighbours with line segments.
Calculation of the border ratio Three types of points: prototypes, class-outliers, and absorbed points. Given a training set X, CNN works iteratively: Scan all elements of X, looking for an element x whose nearest prototype from U has a different label than x. Remove x from X and add it to U; Repeat the scan until no more prototypes are added to U.
Otsu's method is related to Fisher's linear discriminant, and was created to binarize the histogram of pixels in a grayscale image by optimally picking the black/white threshold that minimizes intra-class variance and maximizes inter-class variance within/between grayscales assigned to black and white pixel classes.
Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.
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Credence (statistics) – Measure of belief strength used in statistics; Credible interval, a Bayesian alternative for interval estimation; Cumulative distribution function-based nonparametric confidence interval – Class of confidence intervals around statistical functionals of a distribution