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Other polynominal classification tasks, i.e. tasks with more than two classes can be handled by the <A HREF="../../../../com/rapidminer/operator/performance/PolynominalClassificationPerformanceEvaluator.html" title="class in com.rapidminer.operator.performance"><CODE>PolynominalClassificationPerformanceEvaluator</CODE></A> operator. This operator expects a test <A HREF="../../../../com/rapidminer/example/ExampleSet.html" title="interface in com.rapidminer.example"><CODE>ExampleSet</CODE></A> as input, whose elements have both true and predicted labels, and delivers as output a list of performance values according to a list of performance criteria that it calculates. If an input performance vector was already given, this is used for keeping the performance values.</p> <p>All of the performance criteria can be switched on using boolean parameters. Their values can be queried by a ProcessLogOperator using the same names. The main criterion is used for comparisons and need to be specified only for processes where performance vectors are compared, e.g. feature selection or other meta optimization process setups. If no other main criterion was selected, the first criterion in the resulting performance vector will be assumed to be the main criterion.</p> <p>The resulting performance vectors are usually compared with a standard performance comparator which only compares the fitness values of the main criterion. Other implementations than this simple comparator can be specified using the parameter <var>comparator_class</var>. This may for instance be useful if you want to compare performance vectors according to the weighted sum of the individual criteria. In order to implement your own comparator, simply subclass <A HREF="../../../../com/rapidminer/operator/performance/PerformanceComparator.html" title="interface in com.rapidminer.operator.performance"><CODE>PerformanceComparator</CODE></A>. Please note that for true multi-objective optimization usually another selection scheme is
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