Mining Model Columns
Topic Status: Some information in this topic is preview and subject to change in future releases. Preview information describes new features or changes to existing features in Microsoft SQL Server 2016 Community Technology Preview 2 (CTP2).
A data mining model applies a mining model algorithm to the data that is represented by a mining structure. Like the mining structure, the mining model contains columns. A mining model is contained within the mining structure, and inherits all the values of the properties that are defined by the mining structure. The model can use all the columns that the mining structure contains or a subset of the columns.
You can define two additional pieces of information on a mining model column: usage, and modeling flags.
Usage is a property that defines how the model uses the column. Columns can be used as input columns, key columns, or predictable columns.
Modeling flags provide the algorithm with additional information about the data that is defined in the case table, so that the algorithm can build a more accurate model. You can define modeling flags programmatically by using the Data Mining Extensions (DMX) language, or in Data Mining Designer in SQL Server Data Tools (SSDT).
The following list describes the modeling flags that you can define on a mining model column.
For more information about setting the usage property and defining modeling flags programmatically with DMX, see CREATE MINING MODEL (DMX). For more information about setting the usage property and defining modeling flags in SQL Server Data Tools (SSDT), see Moving Data Mining Objects.