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This guide outlines the steps to effectively use RapidMiner for data analysis. First, download and install RapidMiner. Next, create a project and set the data source, typically in ARFF or Excel format. Choose your desired analysis type, such as clustering or classification, and configure the necessary parameters. Finally, execute your analysis and review the results from the output panel. Sample datasets in ARFF format are available on the course website, and additional UCI datasets can be converted to ARFF for use.
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Rapid Miner Session • 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 provide in course website. • Or, Proben Datasets from UCI, you need to change the data format to ARFF before use. Can be found in our website also. CIS 787 Data Mining,EECS, SU
Step 1 • Download and Install Rapid Miner • http://rapid-i.com/content/view/130/82/ • Create a Rapid Miner Project ( click “new” icon ) CIS 787 Data Mining,EECS, SU
Step 1 Setting data source • Set a data source for project , usually is a data file( arff format or excel spread format), we use arff file as example CIS 787 Data Mining,EECS, SU
Step1 Setting data source(cont) • Assign the data file to data source CIS 787 Data Mining,EECS, SU
Step2 Select analysis type • Choose one of the data mining analysis type for project, such as clustering, classification, decision tree, etc. • For example, we choose the clustering. Right click the “Root” menu of left side to select the “simpleKMean” method to do the clustering as below: CIS 787 Data Mining,EECS, SU
Step2 Decide Parameters • Decide the detail parameters for clustering. CIS 787 Data Mining,EECS, SU
Step3 Execute • Execute . click the “ ” button in top side to run the clustering. CIS 787 Data Mining,EECS, SU
Step3 Check results • Check results from output panel. There are many different output panels if you choose different analysis function. CIS 787 Data Mining,EECS, SU