Index
A
- ADP 5.2.3.2
- Advanced Analytics option 8.1.1, A.2
- algorithms 5.1, 5.2.2
- parallel execution 8.1.3
- Algorithms
- ALL_MINING_MODEL_ATTRIBUTES 2.2
- ALL_MINING_MODEL_SETTINGS 2.2, 5.3.4
- ALL_MINING_MODEL_VIEWS 2.2
- ALL_MINING_MODEL_XFORMS 2.2
- ALL_MINING_MODELS 2.2
- anomaly detection 2.1, 3.1.3, 5.2.1, 5.2.2, 6.7
- APPLY 6.1
- Apriori 3.4, 4.3.4, 5.2.2
- example: calculating aggregates 3.5.1
- association rules 5.2.1, 5.2.2
- Association Rules 5.4.1
- attribute importance 2.1, 5.2.1, 5.2.2
- attributes 3.1.1, 3.2, 7.4
- attribute specification 4.4.1, 7.6
- AUDIT 8.4.2, 8.5.2
- Automatic Data Preparation 1.1, 3.1.3, 4.3
C
- case ID 3.1, 3.1.1, 3.2.4, 6.7
- case table 3.1, 4.2
- categorical attributes 7.1
- chopt utility 8.1.2
- classification 2.1, 3.1.2, 3.1.3, 3.2.2, 5.2.1, 5.2.2
- Classification Algorithm 5.4.5
- class weights 5.3.3
- clipping 4.3.3
- CLUSTER_DETAILS 1.4, 2.4
- CLUSTER_DISTANCE 2.4
- CLUSTER_ID 1.4, 2.4
- CLUSTER_PROBABILITY 2.4
- CLUSTER_SET 1.4, 2.4
- clustering 1.4, 2.1, 3.1.3, 5.2.2
- COMMENT 8.4.2
- cost matrix 5.3.1, 6.6, 8.4.3
- cost-sensitive prediction 6.6
- CUR Decomposition 5.2.2
- CUR Matrix Decomposition 5.2.1
D
- data
- Database Upgrade Assistant 8.2.2.1
- data mining
- Data Mining with SQL
- FEATURE_COMPARE
- ESA 1.5
- FEATURE_COMPARE
- Data preparation
- model view
- text features 7.3
- model view
- data types 3.1.1, 4.2.2
- nested 3.3
- DBMS_DATA_MINING 2.3, 5.2.1
- DBMS_DATA_MINING_TRANSFORM 2.3, 2.3.2
- DBMS_PREDICTIVE_ANALYTICS 1.3, 2.3, 2.3.3
- Decision Tree 4.3.4, 5.2.1, 5.2.2, 6.4
- desupported features
- Java API 8.2.1
- directory objects 8.3.3
- DMEIDMSYS 8.2.2.2.1
- downgrading 8.2.4
M
- market basket data 3.4
- MDL 4.3.4
- memory 8.1.3
- Minimum Description Length 4.3.4, 5.2.2, 5.4.20
- mining functions 2.1, 5.1, 5.2.1
- mining models
- missing value treatment 3.6.2
- model attributes
- model details 3.2.6
- Model details
- binning 5.4.21
- Model Detail View
- Model Detail Views 5.4
- models
- model signature 3.2.4
N
P
- parallel execution 6.1, 8.1.3
- Partitioned model 5.2.4
- partitioned model scoring 5.2.4.3
- Partitioned Model
- partitions
- data dictionary 2.2
- PGA 8.1.3
- PL/SQL packages 2.3
- PMML 8.3.6
- PREDICTION 1.2, 1.3, 2.4, 6.5
- GROUPING hint 6.3.4
- PREDICTION_BOUNDS 2.4
- PREDICTION_COST 2.4
- PREDICTION_DETAILS 2.4, 6.5
- PREDICTION_PROBABILITY 1.3, 2.4, 6.4
- PREDICTION_SET 2.4
- predictive analytics 1.1, 1.3, 2.1
- Preparing the Data
- Using Retail Analysis Data
- Aggregates 3.5
- Using Retail Analysis Data
- prior probabilities 5.3.2
- priors table 5.3.2
- privileges 8.3.2, 8.4.1, 8.4.1.1
S
- sample programs 1.1, A.1
- scoring 1.1, 2.1, 6, 8.1.3, 8.4.3
- Scoring Engine 8.2.2.1.1
- settings
- SGA 8.1.3
- Singular Value Decomposition 4.3.4, 5.4.19
- sparse data 3.6
- SQL AUDIT 2.1, 8.5.2
- SQL COMMENT 2.1, 8.5.1
- SQL data mining functions 2.4
- SQL Developer 1.1
- STACK 2.3.2.1, 4.4.2.2
- Static Dictionary Views
- ALL_MINING_MODEL_VIEWS 2.2.5
- Support Vector Machine 4.3.4, 5.2.1, 5.2.2
- SVD 5.2.2
- system privileges 8.4.2, A.2
T
- target 3.2.2, 3.2.3, 3.2.4, 7.4
- test data 3.1.2, 5.1
- text attributes 7.4, 7.6
- text mining 2.3.2.1, 7
- text policy 7.5
- text terms 7.2
- time series 5.2.1, 5.2.2
- training data 5.1
- transactional data 3.1, 3.3.2, 3.4
- Transactional Itemsets 5.4.3
- Transactional rule 5.4.4
- transformations 2.3.2, 3.1.3, 3.2.1, 3.2.6, 5.1, 5.2.3
- transparency 3.2.6
- trimming 4.4.4.3