The size of the training set is defined by a row number percentage from the initial data set. The rows of each set are randomly drawn from the initial dataset. Training and test sets (%): Data are split into two parts – a training set and a test set.The size of the training set is defined by a number of rows. Training and test sets: Data are split into two parts – a training set and a test set.User defined: A variable indicates the frequency of each observation within the output sample.In each stratum, the number of sampled observations is proportional to a relative frequency supplied by the user. Random stratified (3 ): Rows are chosen at random within N strata defined by the user.In each stratum, the number of sampled observations is proportional to the relative frequency of the stratum. Random stratified (2): Rows are chosen at random within N strata defined by the user.Random stratified (1): Rows are chosen at random within N sequences of observations of equal length, where N is determined by dividing the number of observations by the requested sample size.Systematic centered: Observations are chosen systematically in the centers of N sequences of observations of length k.k is determined such that the observations extracted are as spaced out as possible j is chosen at random from among a number of possibilities depending on the size of the initial table and the size of the final sample. Systematic from random start: From the j'th observation in the initial table, an observation is extracted every k observations to be used in the sample.Random with replacement: Observations are chosen at random and may occur several times in the sample. Random without replacement: Observations are chosen at random and may occur only once in the sample.Here, the implemented model is the Simple Retention Model (SRM), suitable. Several models for calculating CLV exist which vary according to multiple factors, specific to each organization. N every s starting at k: The sample is built extracting N rows, every s rows, starting at row k Customer Lifetime Value (CLV) can be defined as the present value of the future cash flows attributed to the relationship between a customer and the company.This method is only used if it is certain that the values have not been sorted according to a particular criterion which could introduce bias into the analysis N last rows: The sample obtained is taken from the last N rows of the initial table. N first rows: The sample obtained is taken from the first N rows of the initial table.XLSTAT offers the following methods for generating a sample of N observations from a table of M rows: To meet these different situations, several methods have been proposed. Obtain very small tables which have the properties of the original table.
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