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specifies the model ID variable name to use when generating SAS score code. By default, DT_ is prefixed to the target variable name....
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specifies the number of bins to use for numeric variables in the calculation of the decision tree.
Default: 50
Minimum value: 1...
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specifies the number of bins to use for a numerical target variable.
Default: 0...
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specifies the nominal input variables to use in the analysis.
For more information about specifying the nominals parameter, see the common casinvardesc parameter.
Alias: nominal

format: specifies the format to apply to the variable.
formattedLength: specifies the length of the format field plus the...
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specifies the method for finding a split on a nominal input.
Alias: nomSearch

handling: CLASSIC | ENHANCED
maxCategories: specifies the maximum number of levels for a splitting rule to include.
Aliases: maxCats, maxLevels, maxValues, cluster, minCardCluster
Default: 128
Minimum value: 0
shrinkage: ...
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specifies the number of trees to create.
Alias: nTrees
Default: 50
Minimum value: 1...
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when set to True, specifies that the out-of-bag error is computed when building a forest. This also generates a result table with the OOB error for each tree.
Default: FALSE...
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specify true to use a C4.5 pruning method for classification trees or minimal cost-complexity pruning for regression trees.
Default: FALSE...
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specifies bin boundaries at quantiles of numerical inputs instead of bins of equal width.
Aliases: qbin, qtbin
Default: TRUE...
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specifies variable importance using the random branch assignments (RBA) method.
Default: FALSE...
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Default: 100
Range: (0–MACINT]...
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specifies the table to store the generated aStore model.
For more information about specifying the saveState parameter, see the common casouttable parameter....
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specifies the seed for the random number generator. By default, the random number stream is based on the computer clock. Negative values also result in random number streams based on the computer clock. If you want a reproducible random number sequence between runs, specify a value that is greater t...
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specifies the settings for an input table.
Long form: table={name="table-name"}
Shortcut form: table="table-name"
The castable value can be one or more of the following:

caslib: specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Spe...
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specifies the target or response variable for training. If the variable is numeric, but not specified in the nominal= parameter and nbinstarget= is not specified, then a regression tree is trained....
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specifies whether the variable importance information is generated. The importance value is determined by the total Gini reduction.
Default: FALSE...
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requests variable interaction importance and specifies the maximum degree of interaction.
Default: 1
Range: 0–3...
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specifies the vote strategy for classification. The specified value influences the generated SAS scoring code and the OOB error computations.
Default: MAJORITY
MAJORITY: specifies to use the majority vote to predict.
PROB: specifies to use the average probability from the forest to predict....
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specifies a numeric variable that contains the weight of each observation....
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The fPca action is designed to perform functional Principal Component Analysis (FPCA) training on data....
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The 'table' parameter is required to specify the settings for the input table....
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You use the 'inputs' parameter (alias 'input') to specify the list of variables for the analysis....
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The 'id' parameter is used to specify the variable that serves as the record identifier....
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You can use the 'saveState' parameter to specify the output data table in which to save the state of the eigenvector matrix....
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The 'nBins' parameter specifies the number of bins to use when binning functional curves. The minimum accepted value is 10....
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The 'eigenVal' parameter specifies the output table for the eigenvalue matrix, and the 'eigenVec' parameter specifies the output table for the eigenvector matrix....
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The default value for the 'rankThreshold' parameter (also aliased as 'threshold') is 1E-08....
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The fPcaScore action is designed to perform functional principal component analysis (FPCA) scoring....
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The "model" parameter is required; it specifies the analytic store (table) resulting from FPCA training....
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You can specify the number of principal components to use by setting the "npc" parameter within the "output" list. The default value is 4....
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The "casout" parameter, specified within the "output" list, determines the output data table where the score values of the scoring data will be saved....
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Yes, the "table" parameter is required to specify the settings for the input table containing the data to be scored....
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The freq action generates a frequency distribution for one or more variables. It allows you to perform basic analytic functions on your data....
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You can use the "casOut" parameter to specify the settings for the output table, such as the table name, caslib, whether to replace an existing table, and compression settings....
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You can set the "includeMissing" parameter to TRUE. This ensures that missing values are included in the determination of distinct values for the frequency analysis....
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Yes, by setting the "raw" parameter to TRUE. When this is enabled, the raw values of the variables are used, and the results are ordered by the raw values, overriding the "rawOrder" parameter....
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You can use the "descending" parameter. If set to TRUE, the levels of the group-by variables are arranged in descending order....
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The "groupByLimit" parameter specifies the maximum number of levels in a group-by set. If the server determines that this limit is reached, it stops the operation and returns no result, which helps avoid creating excessively large result sets....
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You can use the "attributes" parameter to define specific attributes for variables, including their format, formatted length, and label....
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When set to TRUE, the action writes to the output table immediately after each by-group is processed, rather than waiting for all groups to complete....
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The freqTab action is used to construct frequency and crosstabulation tables....
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The 'table' parameter is required to specify the settings for the input table....
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You can set the 'descending' parameter to TRUE to reverse the sort order imposed by the 'order' parameter....
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Set the 'includeMissing' parameter to TRUE to treat missing values as valid levels for the variables defined in the 'tabulate' parameter....
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Yes, by setting the 'includeZeroWeight' parameter to TRUE, observations with weights of 0 are included in the analysis....
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Use the 'order' parameter. Valid values are 'FORMATTED' (external formatted value), 'FREQ' (descending frequency count), or 'INTERNAL' (unformatted value)....
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Use the 'tabulate' parameter. You can specify the 'vars' subparameter for one-way tables, or combine 'vars' and 'cross' subparameters to produce two-way or multiway crosstabulation tables....
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The 'outputTables' parameter is used to list the names of the results tables to save as CAS tables....
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Use the 'weight' parameter to specify the name of a numeric variable that provides a weight for each observation....
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The 'tabDisplay' parameter allows you to control the display. Specifically, the 'format' subparameter can be set to 'CROSSLIST' (separate two-way tables) or 'LIST' (entire multiway crosstabulation in a single table)....
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