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User defined: A variable indicates the frequency of each observation within the output sample.
Training and test sets: Data are split into two parts – a training set and a test set. The rows of each set are randomly drawn from the initial dataset. 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. The rows of each set are randomly drawn from the initial dataset. The size of the training set is defined by a row number percentage from the initial data set.
Use of data sampling
Sampling is one of the fundamental data analysis and statistical techniques. Sampling aims at extracting a sample of size n from a dataset.
In addition to the features of Basic, Basic+ provides machine learning methods (association rules, random forests, k-nearest neighbors, and more). You can also run advanced models such as partial least squares regression, nonlinear regression, or mixed models.
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