Table of Contents
- Title and Copyright Information
- Preface
-
Part I Introductions
- 1 Introduction to Oracle Machine Learning for SQL
- 2 Oracle Machine Learning Basics
-
Part II Machine Learning Techniques
- 3 Regression
- 4 Classification
- 5 Clustering
- 6 Anomaly Detection
- 7 Ranking
- 8 Association
- 9 Feature Selection
- 10 Feature Extraction
- 11 Row Importance
- 12 Time Series
-
Part III Algorithms
- 13 Apriori
- 14 CUR Matrix Decomposition
- 15 Decision Tree
- 16 Expectation Maximization
- 17 Explicit Semantic Analysis
- 18 Exponential Smoothing
- 19 Generalized Linear Model
- 20 k-Means
- 21 Minimum Description Length
- 22 Multivariate State Estimation Technique - Sequential Probability Ratio Test
- 23 Naive Bayes
- 24 Neural Network
- 25 Non-Negative Matrix Factorization
- 26 O-Cluster
- 27 R Extensibility
- 28 Random Forest
- 29 Singular Value Decomposition
- 30 Support Vector Machine
- 31 XGBoost
-
Part IV Using the Oracle Machine Learning for SQL API
- 32 Oracle Machine Learning With SQL
- 33 About the Oracle Machine Learning for SQL API
- 34 Prepare the Data
-
35
Create a Model
- Before Creating a Model
- Automatic Data Preparation
- Embed Transformations in a Model
- Understand Reverse Transformations
- The CREATE_MODEL Procedure
- The CREATE_MODEL2 Procedure
- Specify Model Settings
-
Model Detail Views
- Model Detail Views for Association Rules
- Model Detail View for Frequent Itemsets
- Model Detail Views for Transactional Itemsets
- Model Detail View for Transactional Rule
- Model Detail Views for Classification Algorithms
- Model Detail Views for Decision Tree
- Model Detail Views for Generalized Linear Model
- Model Detail View for Multivariate State Estimation Technique - Sequential Probability Ratio Test
- Model Detail Views for Naive Bayes
- Model Detail Views for Neural Network
- Model Detail Views for Random Forest
- Model Detail View for Support Vector Machine
- Model Detail Views for XGBoost
- Model Detail Views for Clustering Algorithms
- Model Detail Views for Expectation Maximization
- Model Detail Views for k-Means
- Model Detail Views for O-Cluster
- Model Detail Views for CUR Matrix Decomposition
- Model Detail Views for Explicit Semantic Analysis
- Model Detail Views for Exponential Smoothing
- Model Detail Views for Non-Negative Matrix Factorization
- Model Detail Views for Singular Value Decomposition
- Model Detail Views for Minimum Description Length
- Model Detail Views for Binning
- Model Detail Views for Global Information
- Model Detail Views for Normalization and Missing Value Handling
- 36 Scoring and Deployment
- 37 Machine Learning Operations on Unstructured Text
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38
Administrative Tasks for Oracle Machine Learning for SQL
- Install and Configure a Database for Oracle Machine Learning for SQL
- Upgrade or Downgrade Oracle Machine Learning for SQL
- Export and Import Oracle Machine Learning for SQL Models
- Control Access to Oracle Machine Learning for SQL Models and Data
- Audit and Add Comments to Oracle Machine Learning for SQL Models
- 39 Oracle Machine Learning for SQL Examples
-
Part V Oracle Machine Learning for SQL API Reference
-
40
PL/SQL Packages
-
DBMS_DATA_MINING
- Using DBMS_DATA_MINING
-
DBMS_DATA_MINING — Model Settings
- DBMS_DATA_MINING — Algorithm Names
- DBMS_DATA_MINING — Automatic Data Preparation
- DBMS_DATA_MINING — Machine Learning Function Settings
- DBMS_DATA_MINING — Global Settings
- DBMS_DATA_MINING — Algorithm Settings: ALGO_EXTENSIBLE_LANG
- DBMS_DATA_MINING — Algorithm Settings: CUR Matrix Decomposition
- DBMS_DATA_MINING — Algorithm Settings: Decision Tree
- DBMS_DATA_MINING — Algorithm Settings: Expectation Maximization
- DBMS_DATA_MINING — Algorithm Settings: Explicit Semantic Analysis
- DBMS_DATA_MINING — Algorithm Settings: Exponential Smoothing
- DBMS_DATA_MINING — Algorithm Settings: Generalized Linear Model
- DBMS_DATA_MINING — Algorithm Settings: k-Means
- DBMS_DATA_MINING - Algorithm Settings: Multivariate State Estimation Technique - Sequential Probability Ratio Test
- DBMS_DATA_MINING — Algorithm Settings: Naive Bayes
- DBMS_DATA_MINING — Algorithm Settings: Neural Network
- DBMS_DATA_MINING — Algorithm Settings: Non-Negative Matrix Factorization
- DBMS_DATA_MINING — Algorithm Settings: O-Cluster
- DBMS_DATA_MINING — Algorithm Settings: Random Forest
- DBMS_DATA_MINING — Algorithm Constants and Settings: Singular Value Decomposition
- DBMS_DATA_MINING — Algorithm Settings: Support Vector Machine
- DBMS_DATA_MINING — Algorithm Settings: XGBoost
- DBMS_DATA_MINING — Solver Settings
- DBMS_DATA_MINING Datatypes
-
Summary of DBMS_DATA_MINING Subprograms
- ADD_COST_MATRIX Procedure
- ADD_PARTITION Procedure
- ALTER_REVERSE_EXPRESSION Procedure
- APPLY Procedure
- COMPUTE_CONFUSION_MATRIX Procedure
- COMPUTE_CONFUSION_MATRIX_PART Procedure
- COMPUTE_LIFT Procedure
- COMPUTE_LIFT_PART Procedure
- COMPUTE_ROC Procedure
- COMPUTE_ROC_PART Procedure
- CREATE_MODEL Procedure
- CREATE_MODEL2 Procedure
- Create Model Using Registration Information
- DROP_ALGORITHM Procedure
- DROP_PARTITION Procedure
- DROP_MODEL Procedure
- EXPORT_MODEL Procedure
- EXPORT_SERMODEL Procedure
- FETCH_JSON_SCHEMA Procedure
- GET_ASSOCIATION_RULES Function
- GET_FREQUENT_ITEMSETS Function
- GET_MODEL_COST_MATRIX Function
- GET_MODEL_DETAILS_AI Function
- GET_MODEL_DETAILS_EM Function
- GET_MODEL_DETAILS_EM_COMP Function
- GET_MODEL_DETAILS_EM_PROJ Function
- GET_MODEL_DETAILS_GLM Function
- GET_MODEL_DETAILS_GLOBAL Function
- GET_MODEL_DETAILS_KM Function
- GET_MODEL_DETAILS_NB Function
- GET_MODEL_DETAILS_NMF Function
- GET_MODEL_DETAILS_OC Function
- GET_MODEL_SETTINGS Function
- GET_MODEL_SIGNATURE Function
- GET_MODEL_DETAILS_SVD Function
- GET_MODEL_DETAILS_SVM Function
- GET_MODEL_DETAILS_XML Function
- GET_MODEL_TRANSFORMATIONS Function
- GET_TRANSFORM_LIST Procedure
- IMPORT_MODEL Procedure
- IMPORT_SERMODEL Procedure
- JSON Schema for R Extensible Algorithm
- REGISTER_ALGORITHM Procedure
- RANK_APPLY Procedure
- REMOVE_COST_MATRIX Procedure
- RENAME_MODEL Procedure
-
DBMS_DATA_MINING_TRANSFORM
- Using DBMS_DATA_MINING_TRANSFORM
- DBMS_DATA_MINING_TRANSFORM Operational Notes
-
Summary of DBMS_DATA_MINING_TRANSFORM Subprograms
- CREATE_BIN_CAT Procedure
- CREATE_BIN_NUM Procedure
- CREATE_CLIP Procedure
- CREATE_COL_REM Procedure
- CREATE_MISS_CAT Procedure
- CREATE_MISS_NUM Procedure
- CREATE_NORM_LIN Procedure
- DESCRIBE_STACK Procedure
- GET_EXPRESSION Function
- INSERT_AUTOBIN_NUM_EQWIDTH Procedure
- INSERT_BIN_CAT_FREQ Procedure
- INSERT_BIN_NUM_EQWIDTH Procedure
- INSERT_BIN_NUM_QTILE Procedure
- INSERT_BIN_SUPER Procedure
- INSERT_CLIP_TRIM_TAIL Procedure
- INSERT_CLIP_WINSOR_TAIL Procedure
- INSERT_MISS_CAT_MODE Procedure
- INSERT_MISS_NUM_MEAN Procedure
- INSERT_NORM_LIN_MINMAX Procedure
- INSERT_NORM_LIN_SCALE Procedure
- INSERT_NORM_LIN_ZSCORE Procedure
- SET_EXPRESSION Procedure
- SET_TRANSFORM Procedure
- STACK_BIN_CAT Procedure
- STACK_BIN_NUM Procedure
- STACK_CLIP Procedure
- STACK_COL_REM Procedure
- STACK_MISS_CAT Procedure
- STACK_MISS_NUM Procedure
- STACK_NORM_LIN Procedure
- XFORM_BIN_CAT Procedure
- XFORM_BIN_NUM Procedure
- XFORM_CLIP Procedure
- XFORM_COL_REM Procedure
- XFORM_EXPR_NUM Procedure
- XFORM_EXPR_STR Procedure
- XFORM_MISS_CAT Procedure
- XFORM_MISS_NUM Procedure
- XFORM_NORM_LIN Procedure
- XFORM_STACK Procedure
- DBMS_PREDICTIVE_ANALYTICS
-
DBMS_DATA_MINING
- 41 Data Dictionary Views
- 42 SQL Scoring Functions
-
40
PL/SQL Packages