SAP HANA Predictive Analysis Library (PAL)

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INSERT INTO PAL_ARIMA_DATA_TBL VALUES(8 , 6.735 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(9 , -19.365 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(10 , 34.085 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(11 , 52.455 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(12 , 8.445 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(13 , -13.595 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(14 , 36.73 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(15 , 54.81 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(16 , 4.625 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(17 , -15.595 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(18 , 36.61 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(19 , 58.51 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(20 , 6.725 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(21 , -9.815 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(22 , 38.65 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(23 , 55.5 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(24 , 12.415 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(25 , -17.28 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(26 , 36.105 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(27 , 50.43 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(28 , 7.17 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(29 , -18.97 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(30 , 39.775 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(31 , 57.825 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(32 , 0.49 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(33 , -19.475 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(34 , 31.53 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(35 , 50.025 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(36 , 6.47 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(37 , -20.585 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(38 , 36.94 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(39 , 54.37 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(40 , 10.705 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(41 , -15.965 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(42 , 33.415 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(43 , 55.41 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(44 , -0.62 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(45 , -24.52 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(46 , 37.345 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(47 , 59.44 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(48 , 3.91 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(49 , -19.305 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(50 , 39.525 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(51 , 55.545 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(52 , 3.96 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(53 , -21.69 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(54 , 33.255 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(55 , 57.795 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(56 , 7.535 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(57 , -21.865 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(58 , 36.89 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(59 , 52.17 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(60 , 0.94 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(61 , -23.82 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(62 , 35.025 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(63 , 50.5 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(64 , 4.29 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(65 , -15.27 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(66 , 36.335 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(67 , 51.435 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(68 , 3.365 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(69 , -25.535 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(70 , 33.425 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(71 , 52.785 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(72 , 3.95 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(73 , -17.735 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(74 , 31.95 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(75 , 53.555 ); 350 P U B L I C SAP HANA Predictive Analysis Library (PAL) PAL Functions
INSERT INTO PAL_ARIMA_DATA_TBL VALUES(76 , 6.745 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(77 , -20 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(78 , 31.355 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(79 , 54.71 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(80 , 3.835 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(81 , -23.145 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(82 , 35.23 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(83 , 55.1 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(84 , 3.73 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(85 , -17.605 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(86 , 33.9 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(87 , 55.42 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(88 , 3.505 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(89 , -23.895 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(90 , 34.445 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(91 , 55.635 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(92 , 3.595 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(93 , -21.8 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(94 , 33.45 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(95 , 56.54 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(96 , 5.775 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(97 , -21.27 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(98 , 32.14 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(99 , 53.46 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(100 , -1.935 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(101 , -14.275 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(102 , 35.485 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(103 , 57.305 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(104 , 7.325 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(105 , -21.545 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(106 , 34.11 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(107 , 53.885 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(108 , 1.625 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(109 , -15.75 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(110 , 36.58 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(111 , 54.89 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(112 , 3.8 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(113 , -18.035 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(114 , 37.495 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(115 , 51.875 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(116 , -6.58 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(117 , -18.17 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(118 , 33.565 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(119 , 52.605 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(120 , 3.665 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(121 , -26.47 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(122 , 31.495 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(123 , 52.375 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(124 , 2.135 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(125 , -19.87 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(126 , 36.46 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(127 , 53.11 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(128 , 6.64 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(129 , -21.835 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(130 , 34.625 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(131 , 54.61 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(132 , -5.11 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(133 , -17.395 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(134 , 36.685 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(135 , 52.68 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(136 , 1.105 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(137 , -25.42 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(138 , 32.595 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(139 , 51.615 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(140 , 8.525 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(141 , -15.215 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(142 , 34.455 ); INSERT INTO PAL_ARIMA_DATA_TBL VALUES(143 , 56.165 ); SAP HANA Predictive Analysis Library (PAL) PAL Functions P U B L I C 351
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SAP HANA Platform SPS 12 Document V
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Naive Bayes. ......................
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1 What is PAL? SAP HANA’s SQLScri
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2 Getting Started with PAL This sec
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The result will tell you whether th
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● : The name of the schema where
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CREATE COLUMN TABLE PAL_ARIMAX_DATA
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For more information on how to use
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Category PAL Algorithm Built-in Fun
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Category PAL Algorithm Built-in Fun
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The procedure name is the same as s
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● USER1 has been assigned the AFL
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3.1.2 Agglomerate Hierarchical Clus
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Table 13: Name Data Type Default Va
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Name Data Type Default Value Descri
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INSERT INTO DATA_TBL VALUES ('17',
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Prerequisites ● ● The input dat
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INSERT INTO PAL_AD_DATA_TBL VALUES
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The signature table should contain
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CREATE TYPE PAL_KMEANS_CENTERS_T AS
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PAL_CLUSTER_ASSIGNED_TBL: For DBSCA
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For SOM: SET SCHEMA DM_PAL; DROP TY
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PAL_CLUSTER_ASSIGNED_TBL: Related I
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Table 24: Name Data Type Descriptio
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DROP TYPE PAL_CONTROL_T; CREATE TYP
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3.1.6 Gaussian Mixture Model (GMM)
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Table 29: Name Data Type Descriptio
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Output Tables Output format 0: Tabl
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INSERT INTO PAL_GMM_PDATA_TBL VALUE
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Example 2 SET SCHEMA DM_PAL; DROP T
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PAL_GMM_RESULTSMODEL_TBL: 3.1.7 K-M
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Table 43: Table Column Column Data
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INSERT INTO #PAL_CONTROL_TBL VALUES
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PAL_KMEANS_MODEL_TBL: VALIDATEKMEAN
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"V000" DOUBLE, "A0" INTEGER, "A1" I
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Expected Result PAL_SILHOUETTE_RESU
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Table Column Column Data Type Descr
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Example Assume that: ● ● ● DM
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PAL_KMEDIANS_ASSIGN_TBL: 3.1.9 K-Me
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Position Schema Name Table Type Nam
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The input, parameter, and output ta
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INSERT INTO PARAMETERS_TBL VALUES (
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DOCTOPICDIST_TBL: GENERALINFO_TBL:
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Procedure Calling CALL .(, , ) with
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Expected Result DOCTOPICDIST_TBL: 3
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The following parameters are option
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CREATE TYPE PAL_SOM_MODEL_T AS TABL
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PAL_SOM_RESASSIGN_TBL: PAL_SOM_MODE
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INSERT INTO PAL_SLIGHT_SIL_PDATA_TB
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AUC Procedure Generation CALL SYS.A
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Table 85: Name Data Type Default Va
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Example 2 SET SCHEMA DM_PAL; DROP T
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3.2.2 Back Propagation Neural Netwo
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CREATEBPNN This function trains a B
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INSERT INTO PAL_TRAIN_NN_DATA_TBL V
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PAL_TRAIN_NN_RESULT_TBL: PAL_REGRES
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Classification example: SET SCHEMA
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"NAME" VARCHAR(100), "MODEL" CLOB )
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CREATE TYPE PAL_C45_DATA_T AS TABLE
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CART This function is used for clas
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Prerequisites ● ● The target co
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PAL_CHAID_TREEMODEL_TBL: PAL_CHAID_
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INSERT INTO PAL_CM_DATA_TBL VALUES(
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PAL_KNN_RESULTS_TBL: 3.2.8 Logistic
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Procedure Calling CALL .(, , , , )
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PAL_LOGISTICR_STAT_TBL: PAL_LOGISTI
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Procedure Generation CALL SYS.AFLLA
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Assume that: ● ● ● DM_PAL is
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PAL_FLOGISTICR_FITTED_TBL: Related
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Expected Result PAL_LRMC_MODEL_TBL:
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Table 137: Name Data Type Default V
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SAP HANA Predictive Analysis Librar
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CALL SYS.AFLLANG_WRAPPER_PROCEDURE_
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3.2.10 Naive Bayes Naive Bayes is a
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● ● USER1 has been assigned the
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"DOUBLEARGS" DOUBLE, "STRINGARGS" V
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Position Schema Name Table Type Nam
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DROP TABLE CV_LR_FUNC_TBL; CREATE C
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CREATE COLUMN TABLE FUNC_TBL LIKE F
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DROP TABLE EVALUATION_RESULT_TBL; C
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INSERT INTO PAL_PARA_TBL VALUES('TR
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3.2.13 Random Forest The ransom for
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INSERT INTO PAL_RF_DATA_TBL VALUES
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3.2.14 Support Vector Machine Suppo
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Table 168: Name Data Type Descripti
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CREATE TABLE PAL_SVM_PDATA_TBL("POS
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STRINGARGS VARCHAR(100) ); DROP TYP
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Example 3: Support vector classific
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Related Information SAP HANA Smart
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INSERT INTO PAL_GR_PDATA_TBL values
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Procedure Calling CALL .(, , , ) wi
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3.3.2 Bi-Variate Natural Logarithmi
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CREATE LOCAL TEMPORARY COLUMN TABLE
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Where β0…βn are parameters that
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CREATE LOCAL TEMPORARY COLUMN TABLE
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Assume we have m observation pairs
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Example 1: Fitting multiple linear
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CREATE COLUMN TABLE PAL_ENET_MLR_PD
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3.3.5 Polynomial Regression Polynom
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insert into PAL_PR_PDATA_TBL values
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The input, parameter, and output ta
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3.4 Association Algorithms This sec
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"STRINGARGS" VARCHAR (100) ); INSER
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Optional Parameters The following p
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INSERT INTO PAL_APRIORI_DATA_TBL VA
Page 299 and 300: PAL_APRIORI_CONS_ITEMS_TBL: LITEAPR
Page 301 and 302: Name Data Type Default Value Descri
Page 303 and 304: INSERT INTO PAL_LITEAPRIORI_DATA_TB
Page 305 and 306: Table 233: Table Column Column Data
Page 309 and 310: FPGROWTH (Relational Output) FP-Gro
Page 313 and 314: ); DROP TYPE PAL_FPGROWTH_POSTRULE_
Page 315 and 316: PAL_FPGROWTH_VALUES_TBL: 3.4.3 K-Op
Page 319 and 320: INSERT INTO PAL_KORD_DATA_TBL VALUE
Page 321 and 322: Prerequisite No missing or null dat
Page 323 and 324: . Initial P 0 can be calculated by
Page 325 and 326: Output Table (Model Table) Table 24
Page 327 and 328: DROP TYPE PAL_ARIMAX_DATA_T; CREATE
Page 329 and 330: CALL "SYS".AFLLANG_WRAPPER_PROCEDUR
Page 331 and 332: We get And variance of the forecast
Page 333 and 334: CREATE COLUMN TABLE PAL_ARIMA_PDATA
Page 335 and 336: Table Column Column Data Type Descr
Page 337 and 338: INSERT INTO PAL_ARIMAX_DATA_TBL VAL
Page 339 and 340: 3.5.2 Auto ARIMA This function auto
Page 345 and 346: ● USER1 has been assigned the AFL
Page 347 and 348: CREATE LOCAL TEMPORARY COLUMN TABLE
Page 349: Example 3: Auto Seasonal ARIMA SET
Page 353 and 354: INSERT INTO PAL_ARIMA_DATA_TBL VALU
Page 355 and 356: F 1 = a 0 + b 0 2. Calculation: S t
Page 357 and 358: Table 263: Name Data Type Default V
Page 359 and 360: INSERT INTO PAL_BROWNSMOOTH_DATA_TB
Page 361 and 362: 3.5.4 Croston's Method The Croston
Page 365 and 366: SELECT * FROM PAL_CROSTON_STATISTIC
Page 367 and 368: Table 271: Name Data Type Descripti
Page 369 and 370: PAL_FORECASTACCURACYMEASURES_RESULT
Page 371 and 372: Table 275: Name Data Type Descripti
Page 375 and 376: Table 277: Table Column Column Data
Page 377 and 378: PAL_OUTPARAMETER_TBL: PAL_FORECASTS
Page 379 and 380: PAL_OUTPARAMETER_TBL: SAP HANA Pred
Page 381 and 382: CREATE TYPE PAL_CONTROL_T AS TABLE
Page 383 and 384: PAL_FORECASTTRIPLESMOOTHING_RESULT_
Page 385 and 386: PAL_OUTPARAMETER_TBL: PAL_FORECASTM
Page 387 and 388: PAL_OUTPARAMETER_TBL: PAL_FORECASTM
Page 389 and 390: Procedure Calling CALL .(, , , ) wi
Page 393 and 394: PAL_FORECASTSLR_RESULT_TBL: PAL_FOR
Page 395 and 396: Note The algorithm is backward comp
Page 399 and 400: INSERT INTO #PAL_CONTROL_TBL VALUES
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Note F 0 is not defined because the
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CREATE COLUMN TABLE PAL_DOUBLESMOOT
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3.5.10 Triple Exponential Smoothing
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PAL calculates the prediction inter
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Output Table Table 294: Table Colum
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PAL_TRIPLESMOOTH_RESULT_TBL: PAL_TR
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Once the trend and seasonality are
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CREATE COLUMN TABLE PAL_TSSEASONALI
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The difference-sign test counts the
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Optional Parameters The following p
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PAL_TSTREND_TREND_TBL: PAL_TSTREND_
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Parameter Table Mandatory Parameter
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3.6 Preprocessing Algorithms The re
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● ● Smoothing by bin medians: e
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3.6.2 Binning Assignment Binning as
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3.6.3 Convert Category Type to Bina
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"NAME" VARCHAR(100), "INTARGS" INTE
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Procedure Generation CALL SYS.AFLLA
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INSERT INTO PAL_IQR_TESTDT_TBL VALU
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PARTITION This function reads the i
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3.6.6 Posterior Scaling Posterior s
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Expected Result PAL_NEW_SCALING_TBL
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INSERT INTO PAL_PCA_DATA_TBL VALUES
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INSERT INTO PAL_PCAPROJ_PDATA_TBL V
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INSERT INTO PAL_DISTRRANDOM_PDATA_T
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Table 347: Name Data Type Descripti
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INSERT INTO PAL_SAMPLING_DATA_TBL V
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If method is 4 and SAMPLING_SIZE is
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DROP TABLE PAL_SAMPLING_PDATA_TBL;
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Expected Result 3.6.10 Scaling Rang
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Prerequisite Each column must conta
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PAL_MISSING_VALUES_RESULT_TBL: PAL_
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INSERT INTO PAL_VT_DATA_TBL VALUES
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3.7.2 Chi-Squared Test for Independ
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DISTRPROB This function calculates
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"VALUE" DOUBLE ); DROP TABLE PDATA_
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"DOUBLEARGS" DOUBLE, "STRINGARGS" V
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"TYPE_NAME" NVARCHAR(256), "PARAMET
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2. Calculate PAL also supports the
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The Kaplan-Meier estimator can be r
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PAL_KMSURV_LOGRANK_STAT2_TBL: 3.7.7
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CREATE TYPE PAL_DISTRQUANTILE_RESUL
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where x' = x - Table 404: Definitio
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Let the sample mean of x and y be:
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CREATE TYPE PAL_VAREQUALTEST_DATA1_
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The quantity is computed as a weigh
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Prerequisites ● ● Input data ca
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"PARAMETER_TYPE" VARCHAR(7) ); INSE
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Signature Input Tables Table 425: T
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CALL "SYS".AFLLANG_WRAPPER_PROCEDUR
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"DISTANCE" DOUBLE ); DROP TYPE PAL_
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"STRINGARGS" VARCHAR(100) ); --crea
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The projected estimates are single
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INSERT INTO PDATA VALUES (2, 'DM_PA
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----product revenue---- DELETE FROM
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---- calculate net present value of
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UPDATE PAL_DISTRPROB_DISTRPARAM_TBL
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Then we get the survival estimates
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INSERT INTO PAL_TRIAL_DATA_TBL VALU
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INSERT INTO PAL_DISTRFITCENSORED_DA
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The expected results are as follows
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); INSERT INTO PAL_DISTRPROB_PDATA_
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Important Disclaimers and Legal Inf
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