arff file opened with Note-pad:Dataset Student. The left panel in the above figure shows the list of recognized attributes while the top panel indicates the names of the base relation or table and the current working relation (which are same initially).Step4:Clicking on an attribute in the left panel will show the basic statistics on the attributes for the categorical attributes the frequency of each attribute value is shown, while for continuous attributes we can obtain min, max, mean, standard deviation and deviation etc.,Step5:The visualization in the right button panel in the form of cross-tabulation across two attributes.Dataset Student. We can load the dataset into weka by clicking on open button in preprocessing interface and selecting the appropriate file.Step3: Once the data is loaded, weka will recognize the attributes and during the scan of the data weka will compute some basic strategies on each attribute. Open the Student file and converted arff file is as follows: CSV (Comma Separated Values)Open the saved Student.xls and save as csv.We generate Student.csv file. Open WEKA tool and then Click on Tools- ArffViewer. Step1: Take the existing Student data set and save it as CSV(Macintosh). The sample dataset used for this example is the student data available in arff format.EXCEL sheet Create new excel sheet Student.xlsEnter the tables and save it. Demonstration of preprocessing on dataset student.arffAim: This experiment illustrates some of the basic data preprocessing operations that can be performed using WEKA-Explorer.
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