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Using Naive Bayes in XLMiner™: In XLMiner™, select Classification -> Naive Bayes. Clicking on the Naive Bayes option the following dialog appears. In this dialog the user needs to specify the data range that needs to be processed. The user will then have to specify the input variables and the output variable.
Variables: This box lists all the variables present in the dataset. If the "First row contains headers" box is checked, the header row above the data is used to identify variable names. Variables in input data: Select one or more variables as independent variables from the Variables box by clicking on the corresponding selection button. These variables constitute the predictor variables. Output Variable: Select one variable as the dependent variable from the Variables box by clicking on the corresponding selection button. This is the variable being classified. Specify "Success" class : Let us enter a value "1" here. Then, if in a record the output variable attains a value of 1 in the training data, that is taken as success. Specify initial cutoff probability value for success : Enter the desired value here, say 0.5. Then the class is taken to be a success if the probability is greater than this value. Click Next, and the following dialog box comes up. In this dialog the user can choose the method to calculate the prior class probabilities.
Click Next, and the following dialog box comes up. In this dialog the user can choose to score on the validation data and classify the new observations.
Score training data: Select this option to show an assessment of the performance in classifying the training data. The report is displayed according to your specifications - Detailed, Summary and Lift charts. Score validation data: Select this option to show an assessment of the performance in classifying the validation data. The report is displayed according to your specifications - Detailed, Summary and Lift charts. Score Test Data: The options in this group let you apply the model for scoring to the test partition (if one had been created earlier). The option "Score Test Data" is available only if the dataset contains test partition. Select it to apply the model to test data. Score new Data: The options in this group let you apply the model for scoring to an altogether new data. Specify where the new data is located. See the Example of Discriminant Analysis for detailed instructions on this. Score New data in database : See the Example of Discriminant Analysis for detailed instructions on this. Clicking the Finish button of the dialog box above the output will be computed as per the inputs given in the dialogs above. See also |
