SAP HANA Predictive Analysis Library (PAL)

CV_LR_PARA_SEL_TBL:
Example 2: Naive Bayes
SET SCHEMA DM_PAL;
DROP TYPE FUNC_T;
CREATE TYPE FUNC_T AS TABLE(
"ID" INTEGER,
"Function" VARCHAR(50)
);
DROP TYPE EVALUATION_RESULT_T;
CREATE TYPE EVALUATION_RESULT_T AS TABLE(
"ID" INTEGER,
"Name" VARCHAR(50),
"Value" VARCHAR(5000)
);
DROP TYPE SELECTED_PARAMETER_T;
CREATE TYPE SELECTED_PARAMETER_T AS TABLE(
"ID" INTEGER,
"Name" VARCHAR(50),
"Value" VARCHAR(50)
);
DROP TYPE PAL_NBCTRAIN_TRAININGSET_T;
CREATE TYPE PAL_NBCTRAIN_TRAININGSET_T AS TABLE(
"ID" VARCHAR (10),
"HomeOwner" VARCHAR (100),
"MaritalStatus" VARCHAR (100),
"AnnualIncome" DOUBLE,
"DefaultedBorrower" VARCHAR (100)
);
DROP TYPE PAL_CONTROL_T;
CREATE TYPE PAL_CONTROL_T AS TABLE(
"NAME" VARCHAR (100),
"INTARGS" INTEGER,
"DOUBLEARGS" DOUBLE,
"STRINGARGS" VARCHAR (100)
);
DROP TYPE PAL_NBC_MODEL_T;
CREATE TYPE PAL_NBC_MODEL_T AS TABLE(
"ID" INTEGER,
"JSONSTRING" VARCHAR(5000)
);
DROP TABLE PAL_NBCTRAIN_PDATA_TBL;
CREATE COLUMN TABLE PAL_NBCTRAIN_PDATA_TBL(
"POSITION" INT,
"SCHEMA_NAME" NVARCHAR(256),
"TYPE_NAME" NVARCHAR(256),
"PARAMETER_TYPE" VARCHAR(7)
);
INSERT INTO PAL_NBCTRAIN_PDATA_TBL VALUES (1, 'DM_PAL', 'FUNC_T', 'IN');
INSERT INTO PAL_NBCTRAIN_PDATA_TBL VALUES (2, 'DM_PAL',
'PAL_NBCTRAIN_TRAININGSET_T', 'IN');
INSERT INTO PAL_NBCTRAIN_PDATA_TBL VALUES (3, 'DM_PAL', 'PAL_CONTROL_T', 'IN');
INSERT INTO PAL_NBCTRAIN_PDATA_TBL VALUES (4, 'DM_PAL', 'EVALUATION_RESULT_T',
'OUT');
INSERT INTO PAL_NBCTRAIN_PDATA_TBL VALUES (5, 'DM_PAL', 'SELECTED_PARAMETER_T',
'OUT');
INSERT INTO PAL_NBCTRAIN_PDATA_TBL VALUES (6, 'DM_PAL', 'PAL_NBC_MODEL_T',
'OUT');
CALL "SYS".AFLLANG_WRAPPER_PROCEDURE_DROP('DM_PAL', 'PAL_PSME_NBC_PROC');
CALL "SYS".AFLLANG_WRAPPER_PROCEDURE_CREATE('AFLPAL', 'PSME', 'DM_PAL',
'PAL_PSME_NBC_PROC', PAL_NBCTRAIN_PDATA_TBL);
DROP TABLE FUNC_TBL;
210 P U B L I C
SAP HANA Predictive Analysis Library (PAL)
PAL Functions