FEATURE_VALUE

Syntax

feature_value::=

Analytic Syntax

feature_value_analytic::=

mining_attribute_clause:=

mining_analytic_clause::=

Purpose

FEATURE_VALUE returns a feature value for each row in the selection. The value refers to the highest value feature or to the specified feature_id. The feature value is returned as BINARY_DOUBLE.

Syntax Choice

FEATURE_VALUE can score the data in one of two ways: It can apply a mining model object to the data, or it can dynamically mine the data by executing an analytic clause that builds and applies one or more transient mining models. Choose Syntax or Analytic Syntax:

• Syntax — Use the first syntax to score the data with a pre-defined model. Supply the name of a feature extraction model.

• Analytic Syntax — Use the analytic syntax to score the data without a pre-defined model. Include INTO n, where n is the number of features to extract, and mining_analytic_clause, which specifies if the data should be partitioned for multiple model builds. The mining_analytic_clause supports a query_partition_clause and an order_by_clause. (See "analytic_clause::=".)

mining_attribute_clause

mining_attribute_clause identifies the column attributes to use as predictors for scoring. When the function is invoked with the analytic syntax, this data is also used for building the transient models. The mining_attribute_clause behaves as described for the PREDICTION function. (See "mining_attribute_clause::=".)

Example

The following example lists the customers that correspond to feature 3, ordered by match quality.

SELECT *
 FROM (SELECT cust_id, FEATURE_VALUE(nmf_sh_sample, 3 USING *) match_quality
 FROM nmf_sh_sample_apply_prepared
 ORDER BY match_quality DESC)
 WHERE ROWNUM < 11;
 CUST_ID MATCH_QUALITY
---------- -------------
 100210 19.4101627
 100962 15.2482251
 101151 14.5685197
 101499 14.4186292
 100363 14.4037396
 100372 14.3335148
 100982 14.1716545
 101039 14.1079914
 100759 14.0913761
 100953 14.0799737