Write ARFF
(Advanced File Connectors)
Synopsis
This operator is used for writing an ARFF file.Description
This operator can write data in form of ARFF (Attribute-Relation File Format) files known from the machine learning library Weka. An ARFF file is an ASCII text file that describes a list of instances sharing a set of attributes. ARFF files were developed by the Machine Learning Project at the Department of Computer Science of The University of Waikato for use with the Weka machine learning software. Please study the attached Example Processes for understanding the basics and structure of the ARFF file format. Please note that when an ARFF file is written, the roles of the attributes are not stored. Similarly when an ARFF file is read, the roles of all the attributes are set to regular.
Input
input (Data Table)This input port expects an ExampleSet. It is the output of the Retrieve operator in the attached Example Process.
Output
- through (Data Table)
The ExampleSet that was provided at the input port is delivered through this output port without any modifications. This is usually used to reuse the same ExampleSet in further operators of the process.
file (File)This port buffers the file object for passing it to the reader operators
Parameters
- example_set_fileThe path of the ARFF file is specified here. It can be selected using the choose a file button. Range: filename
- encodingThis is an expert parameter. A long list of encoding is provided; users can select any of them. Range: selection
Tutorial Processes
The basics of ARFF
The 'Iris' data set is loaded using the Retrieve operator. The Write ARFF operator is applied on it to write the 'Iris' data set into an ARFF file. The example set file parameter is set to '%{tempdir}/Iris.txt'. Thus an ARFF file is created in a temp folder of your computer with the name 'Iris'. Open this file to see the structure of an ARFF file.
ARFF files have two distinct sections. The first section is the Header information, which is followed by the Data information. The Header of the ARFF file contains the name of the Relation and a list of the attributes. The name of the Relation is specified after the @RELATION statement. The Relation is ignored by RapidMiner. Each attribute definition starts with the @ATTRIBUTE statement followed by the attribute name and its type. The resultant ARFF file of this Example Process starts with the Header. The name of the relation is 'RapidMinerData'. After the name of the Relation, six attributes are defined.
Attribute declarations take the form of an ordered sequence of @ATTRIBUTE statements. Each attribute in the data set has its own @ATTRIBUTE statement which uniquely defines the name of that attribute and its data type. The order of declaration of the attributes indicates the column position in the data section of the file. For example, in the resultant ARFF file of this Example Process the 'label' attribute is declared at the end of all other attribute declarations. Therefore values of the 'label' attribute are in the last column of the Data section.
The possible attribute types in ARFF are: numeric integer real {nominalValue1,nominalValue2,...} for nominal attributes string for nominal attributes without distinct nominal values (it is however recommended to use the nominal definition above as often as possible) date [date-format] (currently not supported by RapidMiner)
You can see in the resultant ARFF file of this Example Process that the attributes 'a1', 'a2', 'a3' and 'a4' are of real type. The attributes 'id' and 'label' are of nominal type. The distinct nominal values are also specified with these nominal attributes.
The ARFF Data section of the file contains the data declaration line @DATA followed by the actual example data lines. Each example is represented on a single line, with carriage returns denoting the end of the example. Attribute values for each example are delimited by commas. They must appear in the order that they were declared in the Header section (i.e. the data corresponding to the n-th @ATTRIBUTE declaration is always the n-th field of the example line). Missing values are represented by a single question mark (?).
A percent sign (%) introduces a comment and will be ignored during reading. Attribute names or example values containing spaces must be quoted with single quotes ('). Please note that in RapidMiner the sparse ARFF format is currently only supported for numerical attributes. Please use one of the other options for sparse data files provided by RapidMiner if you also need sparse data files for nominal attributes.
Reading an ARFF file using the Read ARFF operator
The ARFF file that was written in the first Example Process using the Write ARFF operator is retrieved in this Example Process using the Read ARFF operator. The data file parameter is set to '%{tempdir}/Iris.txt'. All other parameters are used with default values. Run the process. You will see that the results are very similar to the original Iris data set of RapidMiner repository. Please note that the role of all the attributes is regular in the results of the Read ARFF operator. Even the roles of 'id' and 'label' attributes are set to regular. This is so because the ARFF files do not store information about the roles of the attributes.
