PREDICT BY

Description

Uses a trained model to perform prediction tasks.

Precautions

The name of the invoked model can be viewed in the gs_model_warehouse system catalog.

Syntax

PREDICT BY model_name (FEATURES attribute [, attribute]...);

Parameters

model_name
Name of the model of a speculative task.

Value range: a string. It must comply with the naming convention.
attribute
Name of the input feature column of a speculative task.

Value range: a string. It must comply with the naming convention.

Examples

-- Create a data table.
gaussdb=# CREATE TABLE houses (
id INTEGER,
tax INTEGER,
bedroom INTEGER,
bath DOUBLE PRECISION,
price INTEGER,
size INTEGER,
lot INTEGER,
mark text
);

-- Insert training data.
gaussdb=# INSERT INTO houses(id, tax, bedroom, bath, price, size, lot, mark) VALUES
(1,590,2,1,50000,770,22100,'a+'),
(2,1050,3,2,85000,1410,12000,'a+'),
(3,20,2,1,22500,1060,3500,'a-'),
(4,870,2,2,90000,1300,17500,'a+'),
(5,1320,3,2,133000,1500,30000,'a+'),
(6,1350,2,1,90500,850,25700,'a-'),
(7,2790,3,2.5,260000,2130,25000,'a+'),
(8,680,2,1,142500,1170,22000,'a-'),
(9,1840,3,2,160000,1500,19000,'a+'),
(10,3680,4,2,240000,2790,20000,'a-'),
(11,1660,3,1,87000,1030,17500,'a+'),
(12,1620,3,2,118500,1250,20000,'a-'),
(13,3100,3,2,140000,1760,38000,'a+'),
(14,2090,2,3,148000,1550,14000,'a-'),
(15,650,3,1.5,65000,1450,12000,'a-');

-- Train the model.
gaussdb=# CREATE MODEL price_model USING logistic_regression
 FEATURES size, lot
 TARGET mark
 FROM HOUSES
 WITH learning_rate=0.88, max_iterations=default;

-- Predict.
gaussdb=# SELECT id, PREDICT BY price_model (FEATURES size,lot) FROM houses;

-- Delete the model.
gaussdb=# DROP MODEL price_model;

-- Delete the table.
gaussdb=# DROP TABLE houses;