The model signature is the set of data attributes that are used to build a model. Some or all of the attributes in the signature should be present for scoring. The model accounts for any missing columns on a best-effort basis. If columns with the same names but different data types are present, the model attempts to convert the data type. If extra, unused columns are present, they are disregarded.
The model signature does not necessarily include all the columns in the build data. Algorithm-specific criteria may cause the model to ignore certain columns. Other columns may be eliminated by transformations. Only the data attributes actually used to build the model are included in the signature.
The target and case ID columns are not included in the signature.