Train a model from PostgreSQL database
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 schema and tables
Note that after connecting MindsDB and PostgreSQL, on start, the MindsDB server will automatically create the mindsDB schema and add the predictors table.
Prerequisite
Don't forget to install the MySQL foreign data wrapper as explained in connect your data section.
The INSERT
query for training a new model is quite simple, e.g.:
INSERT INTO mindsdb.predictors(name, predict, select_data_query, training_options)
VALUES ('model_name', 'target_variable', 'SELECT * FROM table_name', '{"additional_training_params:value"}');
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 psql client. The table used for training the model is the Airline Passenger Satisfaction dataset.
INSERT INTO mindsdb.predictors(name, predict, select_data_query) VALUES('airline_survey_model', 'satisfaction', 'SELECT * FROM airline_passenger_satisfaction');
INSERT
query will train a new model called airline_survey_model
that predicts the passenger satisfaction
value.
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.:
SELECT * FROM mindsdb.predictors WHERE name='<model_name>';
That's it
You have successfully trained a new model from PostgreSQL database. The next step is to get predictions by querying the model.