Table of Contents
- Title and Copyright Information
-
1
Overview
- Machine Learning Overview
-
Machine Learning Techniques and Algorithms
- Machine Learning Techniques
- What is a Machine Learning Algorithm
- About Unstructured Text
- About Partitioned Models
- Automatic Data Preparation
- Data Preparation
- Machine Learning Process
- About Oracle Machine Learning for SQL
- 2 Get Started
-
3
Develop
- Interfaces to Oracle Machine Learning for SQL
- About Transformations
- Before Creating a Model
- The CREATE_MODEL2 Procedure
- The CREATE_MODEL Procedure
- About Scoring and Deployment
- 4 Use cases
- 5 Examples
-
6
Reference
- Specify Model Settings
- Specify Oracle Machine Learning Model Settings for an R Model
- Model Settings in the Data Dictionary
-
DBMS_DATA_MINING
- DBMS_DATA_MINING Overview
- DBMS_DATA_MINING Security Model
- DBMS_DATA_MINING — Machine Learning Functions
- DBMS_DATA_MINING — Model Settings
-
DBMS_DATA_MINING — Algorithm Specific Model 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_ONNX_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
- DBMS_DATA_MINING_TRANSFORM Overview
- DBMS_DATA_MINING_TRANSFORM Operational Notes
- DBMS_DATA_MINING_TRANSFORM Security Model
- DBMS_DATA_MINING_TRANSFORM Datatypes
- DBMS_DATA_MINING_TRANSFORM Constants
-
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
-
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 CUR Matrix Decomposition
- 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 Explicit Semantic Analysis
- 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
- Model Detail Views for Exponential Smoothing
- Model Detail Views for Text Features
- Model Detail Views for ONNX Models
- Overview of Database Analytics
-
7
Concepts
-
Machine Learning
Techniques
- About Anomaly Detection
- About Association
- About Classification
- About Clustering
- Embedding
- About Feature Extraction
- Finding the Attributes
- About Ranking
- About Regression
- About Row Importance
- About Time Series
-
Machine Learning
Algorithms
- About Apriori
- About CUR Matrix Decomposition
- About Decision Tree
- About Expectation Maximization
- About Explicit Semantic Analysis
- About Exponential Smoothing
- About Generalized Linear Model
- About k-Means
- About MDL
- About Multivariate State Estimation Technique - Sequential Probability Ratio Test
- About Naive Bayes
- About Neural Network
- About NMF
- About O-Cluster
- Oracle Machine Learning for SQL with R Extensibility
- About Random Forest
- About Singular Value Decomposition
- About Support Vector Machine
- About XGBoost
- Integration of ONNX Runtime
- Machine Learning and Statistics
- Oracle Machine Learning and Analytic Views
- Oracle Machine Learning and Data Warehousing
-
Machine Learning
Techniques
- 8 Administer
- Glossary