CSE/CIS 787 Analytical Data Mining, Dept. of EECS, SU12015-12-15 Three steps for use  Assign the dataset file first  Assign the analysis type you want.

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Presentation transcript:

CSE/CIS 787 Analytical Data Mining, Dept. of EECS, SU Three steps for use  Assign the dataset file first  Assign the analysis type you want  Execute your analysis by RM, change the type if needed. Sample Datasets You can use the ARFF format datasets, available on:

Step  Download and Install Rapid Miner  Create a Rapid Miner Project ( click “new” icon ) CIS 600 Analytical Data Mining,EECS, SU

Step  Set a data source for project, usually it is a data file( arff format or excel spread format), we use iris data file as an example.  In the left side, right click on the “Root” icon, and choose the “ArffExampleSource” menu to select input datasets as below. Setting data source CIS 600 Analytical Data Mining,EECS, SU

Step  Assign the data file to data source Setting data source(cont) CIS 600 Analytical Data Mining,EECS, SU

Step  Assign label_attribute to arffExampleSource, this parameter will let RapidMiner know which attribute in your data source is the class attribute. Setting lable_attribute CIS 600 Analytical Data Mining,EECS, SU

Step  Choose one of the data mining analysis type for project, such as clustering, classification, decision tree, etc.  For example, we create a choose New Operator-> Learner - >Supervised ->Wake->Tress->W-J48 to create a W-J48 operator. This is decision tree functionality. Select functionality i.e analysis type CIS 600 Analytical Data Mining,EECS, SU

Step  Decide the detail parameters for clustering. Decide Parameters CIS 600 Analytical Data Mining,EECS, SU

Step  Execute. click the “ ” button in top side to run the clustering. Execute CIS 600 Analytical Data Mining,EECS, SU

Step  Check results from output panel. There are different output panels if you choose different analysis function. Check results – text view CIS 600 Analytical Data Mining,EECS, SU

Step  Graph view Check results – graph view CIS 600 Analytical Data Mining,EECS, SU