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Explain time series algorithm in data mining.- The Microsoft Time Series algorithm provides regression algorithms that are optimized for the forecasting of continuous values, such as product sales, over time.
- Whereas other Microsoft algorithms, such as decision trees, require additional columns of new information as input to predict a trend, a time series model does not.
- A time series model can predict trends based only on the original dataset that is used to create the model.
- New data can be added to the model when you make a prediction and automatically incorporate the new data in the trend analysis.
- The combination of the source data and the prediction data is called a series.
- An important feature of the Microsoft Time Series algorithm is that it can perform cross prediction.
- If you train the algorithm with two separate, but related, series, you can use the resulting model to predict the outcome of one series based on the behavior of the other series.
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