Table of Contents
- Title and Copyright Information
- Preface
- Part I Introductions
-
Part II Mining Functions
- 3 Regression
- 4 Classification
- 5 Anomaly Detection
- 6 Clustering
- 7 Association
- 8 Feature Selection and Extraction
- 9 Time Series
-
Part III Algorithms
- 10 Apriori
- 11 CUR Matrix Decomposition
- 12 Decision Tree
- 13 Expectation Maximization
- 14 Explicit Semantic Analysis
- 15 Exponential Smoothing
- 16 Generalized Linear Models
- 17 k-Means
- 18 Minimum Description Length
- 19 Naive Bayes
- 20 Neural Network
- 21 Non-Negative Matrix Factorization
- 22 O-Cluster
- 23 R Extensibility
- 24 Random Forest
- 25 Singular Value Decomposition
- 26 Support Vector Machines
-
Part IV Using the Data Mining API
- 27 Data Mining With SQL
- 28 About the Data Mining API
- 29 Preparing the Data
-
30
Transforming the Data
- 30.1 About Transformations
- 30.2 Preparing the Case Table
- 30.3 Understanding Automatic Data Preparation
- 30.4 Embedding Transformations in a Model
- 30.5 Understanding Reverse Transformations
-
31
Creating a Model
- 31.1 Before Creating a Model
- 31.2 The CREATE_MODEL Procedure
- 31.3 Specifying Model Settings
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31.4
Model Detail Views
- 31.4.1 Model Detail Views for Association Rules
- 31.4.2 Model Detail View for Frequent Itemsets
- 31.4.3 Model Detail View for Transactional Itemsets
- 31.4.4 Model Detail View for Transactional Rule
- 31.4.5 Model Detail Views for Classification Algorithms
- 31.4.6 Model Detail Views for Decision Tree
- 31.4.7 Model Detail Views for Generalized Linear Model
- 31.4.8 Model Detail Views for Naive Bayes
- 31.4.9 Model Detail Views for Neural Network
- 31.4.10 Model Detail Views for Random Forest
- 31.4.11 Model Detail View for Support Vector Machine
- 31.4.12 Model Detail Views for Clustering Algorithms
- 31.4.13 Model Detail Views for Expectation Maximization
- 31.4.14 Model Detail Views for k-Means
- 31.4.15 Model Detail Views for O-Cluster
- 31.4.16 Model Detail Views for CUR Matrix Decomposition
- 31.4.17 Model Detail Views for Explicit Semantic Analysis
- 31.4.18 Model Detail Views for Exponential Smoothing Models
- 31.4.19 Model Detail Views for Non-Negative Matrix Factorization
- 31.4.20 Model Detail Views for Singular Value Decomposition
- 31.4.21 Model Detail View for Minimum Description Length
- 31.4.22 Model Detail View for Binning
- 31.4.23 Model Detail Views for Global Information
- 31.4.24 Model Detail View for Normalization and Missing Value Handling
- 32 Scoring and Deployment
- 33 Mining Unstructured Text
-
34
Administrative Tasks for Oracle Data Mining
- 34.1 Installing and Configuring a Database for Data Mining
- 34.2 Upgrading or Downgrading Oracle Data Mining
- 34.3 Exporting and Importing Mining Models
- 34.4 Controlling Access to Mining Models and Data
- 34.5 Auditing and Adding Comments to Mining Models
- 35 The Data Mining Sample Programs
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Part V Oracle Data Mining API Reference
-
36
PL/SQL Packages
-
36.1
DBMS_DATA_MINING
- 36.1.1 Using DBMS_DATA_MINING
-
36.1.2
DBMS_DATA_MINING — Model Settings
- 36.1.2.1 DBMS_DATA_MINING — Algorithm Names
- 36.1.2.2 DBMS_DATA_MINING — Automatic Data Preparation
- 36.1.2.3 DBMS_DATA_MINING — Mining Function Settings
- 36.1.2.4 DBMS_DATA_MINING — Global Settings
- 36.1.2.5 DBMS_DATA_MINING — Algorithm Settings: ALGO_EXTENSIBLE_LANG
- 36.1.2.6 DBMS_DATA_MINING — Algorithm Settings: CUR Matrix Decomposition
- 36.1.2.7 DBMS_DATA_MINING — Algorithm Settings: Decision Tree
- 36.1.2.8 DBMS_DATA_MINING — Algorithm Settings: Expectation Maximization
- 36.1.2.9 DBMS_DATA_MINING — Algorithm Settings: Explicit Semantic Analysis
- 36.1.2.10 DBMS_DATA_MINING — Algorithm Settings: Exponential Smoothing Models
- 36.1.2.11 DBMS_DATA_MINING — Algorithm Settings: Generalized Linear Models
- 36.1.2.12 DBMS_DATA_MINING — Algorithm Settings: k-Means
- 36.1.2.13 DBMS_DATA_MINING — Algorithm Settings: Naive Bayes
- 36.1.2.14 DBMS_DATA_MINING — Algorithm Settings: Neural Network
- 36.1.2.15 DBMS_DATA_MINING — Algorithm Settings: Non-Negative Matrix Factorization
- 36.1.2.16 DBMS_DATA_MINING — Algorithm Settings: O-Cluster
- 36.1.2.17 DBMS_DATA_MINING — Algorithm Settings: Random Forest
- 36.1.2.18 DBMS_DATA_MINING — Algorithm Constants and Settings: Singular Value Decomposition
- 36.1.2.19 DBMS_DATA_MINING — Algorithm Settings: Support Vector Machine
- 36.1.3 DBMS_DATA_MINING — Solver Settings
- 36.1.4 DBMS_DATA_MINING Datatypes
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36.1.5
Summary of DBMS_DATA_MINING Subprograms
- 36.1.5.1 ADD_COST_MATRIX Procedure
- 36.1.5.2 ADD_PARTITION Procedure
- 36.1.5.3 ALTER_REVERSE_EXPRESSION Procedure
- 36.1.5.4 APPLY Procedure
- 36.1.5.5 COMPUTE_CONFUSION_MATRIX Procedure
- 36.1.5.6 COMPUTE_CONFUSION_MATRIX_PART Procedure
- 36.1.5.7 COMPUTE_LIFT Procedure
- 36.1.5.8 COMPUTE_LIFT_PART Procedure
- 36.1.5.9 COMPUTE_ROC Procedure
- 36.1.5.10 COMPUTE_ROC_PART Procedure
- 36.1.5.11 CREATE_MODEL Procedure
- 36.1.5.12 CREATE_MODEL2 Procedure
- 36.1.5.13 Create Model Using Registration Information
- 36.1.5.14 DROP_ALGORITHM Procedure
- 36.1.5.15 DROP_PARTITION Procedure
- 36.1.5.16 DROP_MODEL Procedure
- 36.1.5.17 EXPORT_MODEL Procedure
- 36.1.5.18 EXPORT_SERMODEL Procedure
- 36.1.5.19 FETCH_JSON_SCHEMA Procedure
- 36.1.5.20 GET_ASSOCIATION_RULES Function
- 36.1.5.21 GET_FREQUENT_ITEMSETS Function
- 36.1.5.22 GET_MODEL_COST_MATRIX Function
- 36.1.5.23 GET_MODEL_DETAILS_AI Function
- 36.1.5.24 GET_MODEL_DETAILS_EM Function
- 36.1.5.25 GET_MODEL_DETAILS_EM_COMP Function
- 36.1.5.26 GET_MODEL_DETAILS_EM_PROJ Function
- 36.1.5.27 GET_MODEL_DETAILS_GLM Function
- 36.1.5.28 GET_MODEL_DETAILS_GLOBAL Function
- 36.1.5.29 GET_MODEL_DETAILS_KM Function
- 36.1.5.30 GET_MODEL_DETAILS_NB Function
- 36.1.5.31 GET_MODEL_DETAILS_NMF Function
- 36.1.5.32 GET_MODEL_DETAILS_OC Function
- 36.1.5.33 GET_MODEL_SETTINGS Function
- 36.1.5.34 GET_MODEL_SIGNATURE Function
- 36.1.5.35 GET_MODEL_DETAILS_SVD Function
- 36.1.5.36 GET_MODEL_DETAILS_SVM Function
- 36.1.5.37 GET_MODEL_DETAILS_XML Function
- 36.1.5.38 GET_MODEL_TRANSFORMATIONS Function
- 36.1.5.39 GET_TRANSFORM_LIST Procedure
- 36.1.5.40 IMPORT_MODEL Procedure
- 36.1.5.41 IMPORT_SERMODEL Procedure
- 36.1.5.42 JSON Schema for R Extensible Algorithm
- 36.1.5.43 REGISTER_ALGORITHM Procedure
- 36.1.5.44 RANK_APPLY Procedure
- 36.1.5.45 REMOVE_COST_MATRIX Procedure
- 36.1.5.46 RENAME_MODEL Procedure
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36.2
DBMS_DATA_MINING_TRANSFORM
- 36.2.1 Using DBMS_DATA_MINING_TRANSFORM
- 36.2.2 DBMS_DATA_MINING_TRANSFORM Operational Notes
-
36.2.3
Summary of DBMS_DATA_MINING_TRANSFORM Subprograms
- 36.2.3.1 CREATE_BIN_CAT Procedure
- 36.2.3.2 CREATE_BIN_NUM Procedure
- 36.2.3.3 CREATE_CLIP Procedure
- 36.2.3.4 CREATE_COL_REM Procedure
- 36.2.3.5 CREATE_MISS_CAT Procedure
- 36.2.3.6 CREATE_MISS_NUM Procedure
- 36.2.3.7 CREATE_NORM_LIN Procedure
- 36.2.3.8 DESCRIBE_STACK Procedure
- 36.2.3.9 GET_EXPRESSION Function
- 36.2.3.10 INSERT_AUTOBIN_NUM_EQWIDTH Procedure
- 36.2.3.11 INSERT_BIN_CAT_FREQ Procedure
- 36.2.3.12 INSERT_BIN_NUM_EQWIDTH Procedure
- 36.2.3.13 INSERT_BIN_NUM_QTILE Procedure
- 36.2.3.14 INSERT_BIN_SUPER Procedure
- 36.2.3.15 INSERT_CLIP_TRIM_TAIL Procedure
- 36.2.3.16 INSERT_CLIP_WINSOR_TAIL Procedure
- 36.2.3.17 INSERT_MISS_CAT_MODE Procedure
- 36.2.3.18 INSERT_MISS_NUM_MEAN Procedure
- 36.2.3.19 INSERT_NORM_LIN_MINMAX Procedure
- 36.2.3.20 INSERT_NORM_LIN_SCALE Procedure
- 36.2.3.21 INSERT_NORM_LIN_ZSCORE Procedure
- 36.2.3.22 SET_EXPRESSION Procedure
- 36.2.3.23 SET_TRANSFORM Procedure
- 36.2.3.24 STACK_BIN_CAT Procedure
- 36.2.3.25 STACK_BIN_NUM Procedure
- 36.2.3.26 STACK_CLIP Procedure
- 36.2.3.27 STACK_COL_REM Procedure
- 36.2.3.28 STACK_MISS_CAT Procedure
- 36.2.3.29 STACK_MISS_NUM Procedure
- 36.2.3.30 STACK_NORM_LIN Procedure
- 36.2.3.31 XFORM_BIN_CAT Procedure
- 36.2.3.32 XFORM_BIN_NUM Procedure
- 36.2.3.33 XFORM_CLIP Procedure
- 36.2.3.34 XFORM_COL_REM Procedure
- 36.2.3.35 XFORM_EXPR_NUM Procedure
- 36.2.3.36 XFORM_EXPR_STR Procedure
- 36.2.3.37 XFORM_MISS_CAT Procedure
- 36.2.3.38 XFORM_MISS_NUM Procedure
- 36.2.3.39 XFORM_NORM_LIN Procedure
- 36.2.3.40 XFORM_STACK Procedure
- 36.3 DBMS_PREDICTIVE_ANALYTICS
-
36.1
DBMS_DATA_MINING
- 37 Data Dictionary Views
-
38
SQL Scoring Functions
- 38.1 CLUSTER_DETAILS
- 38.2 CLUSTER_DISTANCE
- 38.3 CLUSTER_ID
- 38.4 CLUSTER_PROBABILITY
- 38.5 CLUSTER_SET
- 38.6 FEATURE_COMPARE
- 38.7 FEATURE_DETAILS
- 38.8 FEATURE_ID
- 38.9 FEATURE_SET
- 38.10 FEATURE_VALUE
- 38.11 ORA_DM_PARTITION_NAME
- 38.12 PREDICTION
- 38.13 PREDICTION_BOUNDS
- 38.14 PREDICTION_COST
- 38.15 PREDICTION_DETAILS
- 38.16 PREDICTION_PROBABILITY
- 38.17 PREDICTION_SET
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36
PL/SQL Packages