The number of terms to add during an AddTerms cycle. The top results according to RankScores will be added, as selected from the AddWindowSize terms tested in the cycle.

The number of terms to test in each round. If left at 0, this defaults to the number of cores the system has available, which should be most efficient.

The builder object to be optimized.

If ScoreMetric is set to a 'Weighted*' value, the weights for each category are retrieved from this array, indexed by category name. If no category weight is set, it is assumed to be 0.

Note: Weights don't need to add up to 1.

The class name of the current "best" classifier. This value is set during Optimize, or as part of the AddTerms and RemoveTerms methods.

The score of the current classifier. This value is updated by AddTerms and RemoveTerms.

The key to %DeepSee.PMML.Utils.TempResult for the test results of CurrentClassifier.

The domain using which the categorization model is being trained and tested. This assumes the value of the Builder's DomainId property when registering an IKnowBuilder instance as Builder, if not set explicitly.

The maximal decrease in performance the optimizer should accept when trying to remove terms. If removing a term would imply a decrease larger than this figure, it will not be removed. A value of 1 means the maximal score decrease is 1%

The metadata field containing the actual category values to compare predictions against. This assumes the value of the Builder's MetadataField property when registering an IKnowBuilder instance as Builder, if not set explicitly.

The minimal score increase % a term should ensure to be retained for further testing. If the score does not increase by at least this figure, it will be discarded from the list of terms to test. A value of 1 means the minimal score increase should be 1%

The number of terms to remove in a "remove" cycle. Setting this value > 1 assumes the terms deemed irrelevant (and scheduled to be removed) don't influence one another much and removing more in a single cycle will not worsen performance much more than the individual performance changes of each term removal alone.

The ratio of RemoveTerms cycles vs AddTerms cycles. This should be a value between 0 and 1 (inclusive).

Note: Remove cycles take significantly longer than add cycles

The default accuracy metric to use for evaluating test results, as used by RankScores. If set to a 'Weighted*' value, the weights are retrieved from CategoryWeights.

The test set to validate model accuracy increases/decreases against.

If set to a boolean value, defines whether or not to write output to the current device during the Optimize method. If set to a string, it is treated as a global reference to which output needs to be written.

This method does one round of processing, testing AddWindowSize candidate terms and selecting the best pCount terms according to RankScores, unless it wouldn't meet the MinimalScoreIncreas threshold.

If pCount < 0, it defaults to RemoveCount.

This method clears the temporary artifacts the optimizer has created while optimizing, such as the CurrentClassifier class and CurrentTestId test results.

Initializes this Optimizer instance. This method is called automatically as part of Optimize

Loads all terms from the supplied array. If pListIndex is non-zero, the term info is read from that index at each array position. If the term info itself is a list structure as well, it is interpreted as follows: pTerms(n) = $lb(term, type, negationpolicy, matchpolicy)

Loads a list of candidate terms based on a SQL query. The query should return a column named "term" containing the term's value and may return columns named "type", "negation" and "match" to configure the type, negation and count policy for each term being retrieved, respectively.

In at most pMaxSteps steps, the current Builder will be optimized by testing, one at a time, the terms added through LoadTermsSQL and LoadTermsArray, judging which term works best for each test window by the results of RankScores (see also AddTerms). Every (1/) rounds, all terms in the dictionary so far will be tested for their contribution to the current model score and the lowest RemoveCount>RemoveStepRatio) rounds, all terms in the dictionary so far will be tested for their contribution to the current model score and the lowest RemoveCount terms will be removed (see also RemoveTerms).

At the end of the optimization process, in addition to Builder being updated, CurrentClassifier will contain the class name of the last test class used to achieve the best result and pTestId will point to the test results for that class.

Test the impact of removing each term in the current model's TermDictionary individually. The pCount terms for which, after removing it, RankScores still returns the best score (which supposedly implies its contribution was minimial), will be removed from the TermDictionary, unless the decrease in performance surpasses MaximalScoreDecrease.

If pCount < 0, it defaults to RemoveCount.

Saves the CurrentClassifier class to the desired pClassName, so it will not be removed after this Optimizer instance is dropped. If CurrentClassifier is not set or if the class no longer exists for other reasons, the current builder object will create a classifier class based on its current state.