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| OREdm-package | Oracle R Enterprise Data Mining Functions |
| clusterhists | Cluster Histogram Data from Clustering Models |
| clusterhists.ore.odmEM | Cluster Histogram Data from Clustering Models |
| clusterhists.ore.odmKMeans | Cluster Histogram Data from Clustering Models |
| clusterhists.ore.odmOC | Cluster Histogram Data from Clustering Models |
| coef | In-Database Support Vector Machine Models |
| coef.ore.odmSVM | In-Database Support Vector Machine Models |
| confint | In-Database Generalized Linear Models |
| confint.ore.odmGLM | In-Database Generalized Linear Models |
| d | In-Database Singular Value Decomposition Models |
| d.ore.odmSVD | In-Database Singular Value Decomposition Models |
| deviance | In-Database Generalized Linear Models |
| deviance.ore.odmGLM | In-Database Generalized Linear Models |
| extractAIC | In-Database Generalized Linear Models |
| extractAIC.ore.odmGLM | In-Database Generalized Linear Models |
| features | In-Database Non-Negative Matrix Factorization Models |
| features.ore.odmESA | In-Database Explicit Semantic Analysis Models |
| features.ore.odmNMF | In-Database Non-Negative Matrix Factorization Models |
| features.ore.odmSVD | In-Database Singular Value Decomposition Models |
| feature_compare | In-Database Non-Negative Matrix Factorization Models |
| feature_compare.ore.odmESA | In-Database Explicit Semantic Analysis Models |
| feature_compare.ore.odmNMF | In-Database Non-Negative Matrix Factorization Models |
| feature_compare.ore.odmSVD | In-Database Singular Value Decomposition Models |
| fitted.ore.odmGLM | In-Database Generalized Linear Models |
| histogram | In-Database Hierarchical K-Means Models |
| histogram.ore.odmEM | In-Database Expectation Maximization Models |
| histogram.ore.odmKMeans | In-Database Hierarchical K-Means Models |
| histogram.ore.odmOC | In-Database Orthogonal Partitioning Cluster Models |
| itemsets | In-Database Association Rules Models |
| itemsets.ore.odmAssocRules | In-Database Association Rules Models |
| logLik | In-Database Generalized Linear Models |
| logLik.ore.odmGLM | In-Database Generalized Linear Models |
| nobs | In-Database Generalized Linear Models |
| nobs.ore.odmGLM | In-Database Generalized Linear Models |
| ore.itemsets | Class 'ore.itemsets' |
| ore.itemsets-class | Class 'ore.itemsets' |
| ore.odmAI | In-Database Attribute Importance Ranking Models |
| ore.odmAssocRules | In-Database Association Rules Models |
| ore.odmDT | In-Database Decision Tree Models |
| ore.odmEM | In-Database Expectation Maximization Models |
| ore.odmESA | In-Database Explicit Semantic Analysis Models |
| ore.odmGLM | In-Database Generalized Linear Models |
| ore.odmKMeans | In-Database Hierarchical K-Means Models |
| ore.odmNB | In-Database Naive Bayes Models |
| ore.odmNMF | In-Database Non-Negative Matrix Factorization Models |
| ore.odmOC | In-Database Orthogonal Partitioning Cluster Models |
| ore.odmRAlg | Extensible R Algorithm Models |
| ore.odmSVD | In-Database Singular Value Decomposition Models |
| ore.odmSVM | In-Database Support Vector Machine Models |
| ore.pull-method | Class 'ore.itemsets' |
| ore.pull-method | Class 'ore.rules' |
| ore.rules | Class 'ore.rules' |
| ore.rules-class | Class 'ore.rules' |
| OREdm | Oracle R Enterprise Data Mining Functions |
| partitions | Partitions and Settings of an Oracle Data Mining Model Object |
| partitions.ore.odmPart | Partitions and Settings of an Oracle Data Mining Model Object |
| predict | In-Database Generalized Linear Models |
| predict.ore.odmDT | In-Database Decision Tree Models |
| predict.ore.odmEM | In-Database Expectation Maximization Models |
| predict.ore.odmESA | In-Database Explicit Semantic Analysis Models |
| predict.ore.odmGLM | In-Database Generalized Linear Models |
| predict.ore.odmKMeans | In-Database Hierarchical K-Means Models |
| predict.ore.odmNB | In-Database Naive Bayes Models |
| predict.ore.odmNMF | In-Database Non-Negative Matrix Factorization Models |
| predict.ore.odmOC | In-Database Orthogonal Partitioning Cluster Models |
| predict.ore.odmRAlg | Extensible R Algorithm Models |
| predict.ore.odmSVD | In-Database Singular Value Decomposition Models |
| predict.ore.odmSVM | In-Database Support Vector Machine Models |
| print.ore.odmAssocRules | In-Database Association Rules Models |
| print.ore.odmEM | In-Database Expectation Maximization Models |
| print.ore.odmGLM | In-Database Generalized Linear Models |
| print.ore.odmKMeans | In-Database Hierarchical K-Means Models |
| print.ore.odmOC | In-Database Orthogonal Partitioning Cluster Models |
| print.ore.odmRAlg | Extensible R Algorithm Models |
| print.ore.odmSVM | In-Database Support Vector Machine Models |
| print.summary.ore.odmAssocRules | Summarize In-Database Association Models |
| print.summary.ore.odmDT | Summarize In-Database Decision Tree Models |
| print.summary.ore.odmEM | Summarize In-Database Expectation Maximization Models |
| print.summary.ore.odmESA | Summarize In-Database Explicit Semantic Analysis Models |
| print.summary.ore.odmGLM | Summarize In-Database Generalized Linear Models |
| print.summary.ore.odmKMeans | Summarize In-Database Hierarchical K-Means Models |
| print.summary.ore.odmNB | Summarize In-Database Naive Bayes Models |
| print.summary.ore.odmNMF | Summarize In-Database Non-Negative Matrix Factorization Models |
| print.summary.ore.odmOC | Summarize In-Database Orthogonal Partitioning Cluster Models |
| print.summary.ore.odmRAlg | Extensible R Algorithm Models |
| print.summary.ore.odmSVD | Summarize In-Database Singular Value Decomposition Models |
| print.summary.ore.odmSVM | Summarize In-Database Support Vector Machine Models |
| residuals | In-Database Generalized Linear Models |
| residuals.ore.odmGLM | In-Database Generalized Linear Models |
| rules | Predicate Rule Data for Clusters or Association Rules Models |
| rules.ore.odmAssocRules | Predicate Rule Data for Clusters or Association Rules Models |
| rules.ore.odmEM | Predicate Rule Data for Clusters or Association Rules Models |
| rules.ore.odmKMeans | Predicate Rule Data for Clusters or Association Rules Models |
| rules.ore.odmOC | Predicate Rule Data for Clusters or Association Rules Models |
| settings | Partitions and Settings of an Oracle Data Mining Model Object |
| settings.ore.model | Partitions and Settings of an Oracle Data Mining Model Object |
| subset-method | Class 'ore.itemsets' |
| subset-method | Class 'ore.rules' |
| summary.ore.odmAssocRules | Summarize In-Database Association Models |
| summary.ore.odmDT | Summarize In-Database Decision Tree Models |
| summary.ore.odmEM | Summarize In-Database Expectation Maximization Models |
| summary.ore.odmESA | Summarize In-Database Explicit Semantic Analysis Models |
| summary.ore.odmGLM | Summarize In-Database Generalized Linear Models |
| summary.ore.odmKMeans | Summarize In-Database Hierarchical K-Means Models |
| summary.ore.odmNB | Summarize In-Database Naive Bayes Models |
| summary.ore.odmNMF | Summarize In-Database Non-Negative Matrix Factorization Models |
| summary.ore.odmOC | Summarize In-Database Orthogonal Partitioning Cluster Models |
| summary.ore.odmRAlg | Extensible R Algorithm Models |
| summary.ore.odmSVD | Summarize In-Database Singular Value Decomposition Models |
| summary.ore.odmSVM | Summarize In-Database Support Vector Machine Models |
| u | In-Database Singular Value Decomposition Models |
| u.ore.odmSVD | In-Database Singular Value Decomposition Models |
| v | In-Database Singular Value Decomposition Models |
| v.ore.odmSVD | In-Database Singular Value Decomposition Models |