Train a model from Microsoft SQL Server
Train new model
To train a new model, you will need to
INSERT a new record inside the mindsdb.predictors table.
How to create the mindsb.predictors table
Note that after connecting the MindsDB and Microsoft SQL server, on start, the MindsDB server will automatically create the mindsdb database and add the predictors table.
Don't forget to install the prerequisites as explained in connect your data section.
There are both options for training the model by using the
exec statement. The
INSERT query for training new model using
exec ('INSERT INTO mindsdb.predictors (name, predict, select_data_query) VALUES (''model_name'', ''target_variable'', ''SELECT * FROM table_name'')') AT mindsdb;
INSERT openquery(mindsdb,'SELECT name, predict, select_data_query FROM mindsdb.predictors WHERE 1=0') VALUES ('model_name','target_variable','SELECT * FROM table_name');
The values provided in the
INSERT query are:
- name (string) -- The name of the model.
- predict (string) -- The feature you want to predict. To predict multiple features, include a comma separated string, e.g. 'feature1,feature2'.
- select_data_query (string) -- The SELECT query that will ingest the data to train the model.
- training_options (JSON as comma separated string) -- optional value that contains additional training parameters. For a full list of parameters, check the PredictorInterface.
Train new model example
The following example shows you how to train a new model from a mssql client. The table used for training the model is the Medical insurance dataset.
exec ('INSERT INTO mindsdb.predictors (name, predict, select_data_query) VALUES ("insurance_model", "charges", "SELECT * FROM mindsdb_test.dbo.insurance")') AT mindsdb;
INSERT query will train a new model called
insurance_model that predicts the
Model training status
To check that the training finished successfully, you can
SELECT from the mindsdb.predictors table and get the training status, e.g.:
exec ('SELECT * FROM mindsdb.predictors') AT mindsdb;
mindsdbis the name of the api['mysql]['database'] key from config.json. The default name is
You have successfully trained a new model from a Microsoft SQL Server. The next step is to get predictions by querying the model.