Machine Learning Model Functions - Ocient Documentation

functionality supports these SQL functions for machine learning models.

The scope of a machine learning model is the schema.

Supported Machine Learning Models

Supported machine learning models and reference material are divided into these categories.

For functions to help organize data before training a model, see Data Preparation.

Regression Models

Classification Models

Clustering and Dimension Reduction Models

Ensemble Models

Other Models

For a view of the full list of model options, see Machine Learning Model Options.

Execute a Query Using a Machine Learning Model

To create a machine learning model and manage the model, see Machine Learning Models for the corresponding syntax. After you create the model, you can execute a query using the model with this syntax. Syntax

SQL

SELECT model_name ( expression [, ... ] ) FROM table_reference

Parameter	Data Type	Description
`model_name`	identifier	The name of a machine learning model created using a `CREATE MODEL` SQL statement. The model name must be a valid identifier and reference an existing trained model.
`expression`	identifier string numeric	One or more expressions that serve as input features for the machine learning model evaluation. These expressions must match the expected input schema the model was trained on. Expressions can be any combination of literal values, column names, arithmetic expressions, and function invocations, with parentheses for grouping.
`table_reference`	identifier	The name of a table, view, or subquery that provides the data for model evaluation. The table must contain columns or computed expressions that match the expected input features of the model.

Example Create a table with data for the model.

SQL

CREATE TABLE mldemo.mlr AS (SELECT a.c1 AS x1, b.c1 AS x2, 1 + 2*a.c1 + 3*b.c1 AS y
    FROM sys.dummy10 a, sys.dummy10 b);
Modified 100 rows

Create a multiple linear regression model based on the data.

SQL

CREATE MLMODEL mlr_model TYPE MULTIPLE LINEAR REGRESSION ON (SELECT * FROM mldemo.mlr)
options('metrics' -> 'true');
Modified 0 rows

Execute a SELECT query against the multiple linear regression to see the actual and predicted values. Limit the result set to 10 rows.

SQL

SELECT x1, x2, y AS actual, mlr_model(x1, x2) AS predicted
    FROM mldemo.mlr
    LIMIT 10;

Output

Text

x1         x2         actual              predicted
----------------------------------------------------------------
        1          16                  15.999999999999975
        2          19                  18.999999999999975
        3          22                  21.999999999999975
        4          25                  24.999999999999975
        5          28                  27.999999999999975
        6          31                  30.999999999999975
        7          34                  33.99999999999997
        8          37                  36.99999999999997
        9          40                  39.99999999999997
        10         43                  42.99999999999997

Fetched 10 rows

Machine Learning in Ocient Machine Learning Models

​Supported Machine Learning Models

​Regression Models

​Classification Models

​Clustering and Dimension Reduction Models

​Ensemble Models

​Other Models

​Execute a Query Using a Machine Learning Model

​Related Links

Supported Machine Learning Models

Regression Models

Classification Models

Clustering and Dimension Reduction Models

Ensemble Models

Other Models

Execute a Query Using a Machine Learning Model

Related Links