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The fism action applies the FP-growth algorithm to identify frequent item sets w...
The faNFactors action determines the number of factors to be retained in a facto...
The annCode action generates SAS DATA step scoring code from a trained artificia...
Classification variables are specified using the 'class' parameter. This allows you to define how these variables are parameterized in the model, including setting the reference level ('ref'), the ordering of levels ('order'), and the parameterization style ('param', e.g., 'EFFECT' or 'GLM').
The `bodySampleFrac` parameter specifies the fraction of points to be sampled from bins that fall in the body region, which is determined by the `tailStart` parameter.
You can use the 'viewOptions' parameter to control the output. It accepts several boolean flags such as 'all', 'minimal', 'finalEstimates', 'correlations', 'fitModelSummary', and 'modelDefinition' to customize which reports are displayed.
You can manage SSL/TLS settings with several boolean parameters. 'sslrequired=TRUE' enforces that all communications use SSL. 'sslallowed=TRUE' permits SSL communication but is ignored if 'sslrequired' is also set to TRUE. Conversely, 'nossl=TRUE' disables SSL/TLS for the data transfer.
Specifies the imputation technique for interval variables. Be aware that you can specify numeric variables as nominal using the nomVarsIndices parameter. Alias: methodContinuous. Default: MEAN. Options: MAX (replaces missing values with the maximum value), MEAN (replaces missing values with the mean), MEDIAN (replaces missing values with the median), MIDRANGE (replaces missing values with the mean of the maximum value and minimum value), MIN (replaces missing values with the minimum value), RANDOM (replaces missing values with uniform random numbers), VALUE (replaces missing values with the values specified in the valuesInterval and valuesNominal parameters).