EMIntro - Click to edit Master subtitle style MIS6324...

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Click to edit Master subtitle style 10/2/11 Enterprise Miner Introduction Syam Menon MIS6324
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10/2/11 Open and Log In 22
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10/2/11 Select New Project 33
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10/2/11 SAS Server Selection 44
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10/2/11 Project Name 55
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10/2/11 SAS Folders (Internal) 66
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10/2/11 Final Step 77
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10/2/11 Initial Screen 88
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10/2/11 SAS Data Mining Process Enterprise Miner nodes are arranged into categories according the SAS process for data mining (SEMMA) Sample : Identify input data sets Identify input data; sample from a larger data set; partition data set into training, validation, and test data sets Explore : Explore data sets statistically and graphically Plot the data, obtain descriptive statistics, identify important variables, perform association analysis Modify : Prepare the data for analysis Create additional variables or transform existing variables for analysis, identify outliers, replace missing values, modify the way in which variables are used for the analysis, perform cluster analysis, etc. Model : Fit a predictive model Model a target variable by using a regression model, a decision tree, a neural network, or a user-defined model 99
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10/2/11 SAS Data Mining Process The Score group Comprises the Score and Score Converter nodes Designed to capture score code for the models and to translate the SAS DATA step score code into the C and Java programming languages SAS DATA step score code can be saved as a SAS program outside Enterprise Miner SAS program can then be run on any platform that runs base SAS Can perform the actual scoring on almost any type of platform Code based on C or Java can be integrated into standalone C or Java programs that operate outside SAS 10
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EMIntro - Click to edit Master subtitle style MIS6324...

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