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ClickHouse/dbms/tests/queries/0_stateless/00945_ml_test.sql

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Logistic Regression and new tests
2019-02-15 22:47:56 +00:00
CREATE DATABASE IF NOT EXISTS test;
DROP TABLE IF EXISTS test.defaults;
CREATE TABLE IF NOT EXISTS test.defaults
(
param1 Float64,
param2 Float64,
target Float64,
predict1 Float64,
predict2 Float64
) ENGINE = Memory;
changes in gradient_computer class
2019-03-03 10:21:12 +00:00
insert into test.defaults values (1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2),(1,2,1,-1,-2),(-1,-2,-1,1,2)
Logistic Regression and new tests
2019-02-15 22:47:56 +00:00
DROP TABLE IF EXISTS test.model;
Remane regression methods.
2019-05-23 11:51:25 +00:00
create table test.model engine = Memory as select logisticRegressionState(0.1, 0.0, 1.0, 'SGD')(target, param1, param2) as state from test.defaults;
Logistic Regression and new tests
2019-02-15 22:47:56 +00:00
linear regression tests
2019-04-08 21:01:10 +00:00
select ans < 1.1 and ans > 0.9 from
(with (select state from test.model) as model select evalMLMethod(model, predict1, predict2) as ans from test.defaults limit 2);
Logistic Regression and new tests
2019-02-15 22:47:56 +00:00
linear regression tests
2019-04-08 21:01:10 +00:00
select ans > -0.1 and ans < 0.1 from
(with (select state from test.model) as model select evalMLMethod(model, predict1, predict2) as ans from test.defaults limit 2);
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