A new feature for Oracle Data Mining in Oracle 12.2 is the new Model Details views.
In Oracle 220.127.116.11 and up to Oracle 12.1 you needed to use a range of PL/SQL functions (in DBMS_DATA_MINING package) to inspect the details of a data mining/machine learning model using SQL.
Check out these previous blog posts for some examples of how to use and extract model details in Oracle 12.1 and earlier versions of the database
Association Rules in ODM-Part 3
Extracting the rules from an ODM Decision Tree model
Viewing Decision Tree Details
Instead of these functions there are now a lot of DB views available to inspect the details of a model. The following table summarises these various DB Views. Check out the DB views I've listed after the table, as these views might some some of the ones you might end up using most often.
I've now chance of remembering all of these and this table is a quick reference for me to find the DB views I need to use. The naming method used is very confusing but I'm sure in time I'll get the hang of them.
NOTE: For the DB Views I've listed in the following table, you will need to append the name of the ODM model to the view prefix that is listed in the table.
describes the scoring cost matrix for Classification models
describes the statistics associated with individual tree nodes
Higher level node description
describes the cost matrix used by the Decision Tree build
describes row level info for Linear Regres & Logistic Regres
describes the conditional probabilities of Naïve Bayes model
Cluster attribute statistics
Cluster historgram statistics
Cluster Rule statistics
k-Means attribute statistics
k-Means historgram statistics
k-Means Rule statistics
O-Cluster attribute statistics
O-Cluster historgram statistics
O-Cluster Rule statistics
the pairwise Kullback–Leibler divergence
attribute ranking similar to that of Attribute Importance
parameters of multi-valued Bernoulli distributions
mean & variance parameters for attributes by Gaussian distribution
the coefficients used by random projections to map nested columns to a lower dimensional space
H inverse matrix for NNMF model
describes the right-singular vectors of SVD model
describes the left-singular vectors of a SVD model
ESA model features
Normalizing and Error Handling views created by ODM Automatic Data Processing (ADP)
Global Model Views
Each one of these new DB views needs their own blog post to explain what informations is being explained in each. I'm sure over time I will get round to most of these.