One of the most important functions of data mining is prediction. In this chapter, you've learned how to find the best mining model for the defined problem and the existing dataset. Microsoft Accuracy Chart provided diagrams such as Classification Matrix, Lift Chart, and Cross Validation, which check the mining model against the test dataset. After finding the best mining model(s), you can use the prediction functionality using the DMX language. You've learned about the DMX query structure and cross-prediction joins with the Prediction Join clause. You've applied the mining model pattern on the case table using DMX queries, and you've learned how to use prediction functions such as PredictProbability to fetch the probability of a predictable variable.

In the last section of this chapter, you saw an example of the Time Series algorithm. You've also learned how to provide input data with time frames to the algorithm. And after configuring and training the algorithm, you ran a DMX query...