# Add attribute values to an existing DataField element in a given PMML file ```r add_data_field_attributes( xml_model = NULL, attributes = NULL, field = NULL, namespace = "4_4", ... ) ``` ## Arguments - `xml_model`: The PMML model in a XML node format. If the model is a text file, it should be converted to an XML node, for example, using the file_to_xml_node function. - `attributes`: The attributes to be added to the data fields. The user should make sure that the attributes being added are allowed in the PMML schema. - `field`: The field to which the attributes are to be added. This is used when the attributes are a vector of name-value pairs, intended for this one field. - `namespace`: The namespace of the PMML model. This is frequently also the PMML version of the model. - ``...``: Further arguments passed to or from other methods. ## Returns An object of class `XMLNode` as that defined by the `XML` package. This represents the top level, or root node, of the XML document and is of type PMML. It can be written to file with `saveXML`. ## Details The PMML schema allows a DataField element to have various attributes, which, although useful, may not always be present in a PMML model. This function makes it possible to add such attributes to DataFields of an existing PMML file. The attribute information can be provided as a dataframe or a vector. Each row of the data frame corresponds to an attribute name and each column corresponding to a variable name. This way one can add as many attributes to as many variables as one wants in one step. A more convenient method to add multiple attributes to one field might be to give the attribute name and values as a vector. This function may be used multiple times to add new attribute values step-by-step. However this function overwrites any pre-existing attribute values, so it must be used with care. This behavior is by design as this feature is meant to help an user add new defined attribute values at different times. For example, one may use this to modify the display name of a field at different times. ## Examples ```r # Make a sample model: fit <- lm(Sepal.Length ~ ., data = iris[, -5]) fit_pmml <- pmml(fit) # The resulting model has mining fields with no information besides # fieldName, dataType and optype. This object is already an xml # node (not an external text file), so there is no need to convert # it to an xml node object. # Create data frame with attribute information: attributes <- data.frame(c("FlowerWidth", 1), c("FlowerLength", 0), stringsAsFactors = FALSE ) rownames(attributes) <- c("displayName", "isCyclic") colnames(attributes) <- c("Sepal.Width", "Petal.Length") # Although not needed in this first try, necessary to easily add # new values later. Removes values as factors so that new values # added later are not evaluated as factor values and thus rejected # as invalid. attributes[] <- lapply(attributes, as.character) fit_pmml_2 <- add_data_field_attributes(fit_pmml, attributes, namespace = "4_4" ) # Alternative method to add attributes to a single field, # "Sepal.Width": fit_pmml_3 <- add_data_field_attributes( fit_pmml, c(displayName = "FlowerWidth", isCyclic = 1), "Sepal.Width" ) mi <- make_intervals( list("openClosed", "closedClosed", "closedOpen"), list(NULL, 1, 2), list(1, 2, NULL) ) mv <- make_values( list("A", "B", "C"), list(NULL, NULL, NULL), list("valid", NULL, "invalid") ) fit_pmml_4 <- add_data_field_children(fit_pmml, field = "Sepal.Length", interval = mi, values = mv ) ``` ## Author(s) Tridivesh Jena

add_data_field_attributes function