AIMA.Core.Learning.Learners.DecisionTreeLearner.decisionTreeLearning C# (CSharp) Метод

        private DecisionTree decisionTreeLearning(DataSet ds,
                List<String> attributeNames, ConstantDecisonTree defaultTree)
        {
            if (ds.size() == 0)
            {
                return defaultTree;
            }
            if (allExamplesHaveSameClassification(ds))
            {
                return new ConstantDecisonTree(ds.getExample(0).targetValue());
            }
            if (attributeNames.Count == 0)
            {
                return majorityValue(ds);
            }
            String chosenAttribute = chooseAttribute(ds, attributeNames);

            DecisionTree tree = new DecisionTree(chosenAttribute);
            ConstantDecisonTree m = majorityValue(ds);

            List<String> values = ds.getPossibleAttributeValues(chosenAttribute);
            foreach (String v in values)
            {
                DataSet filtered = ds.matchingDataSet(chosenAttribute, v);
                List<String> newAttribs = Util.removeFrom(attributeNames,
                        chosenAttribute);
                DecisionTree subTree = decisionTreeLearning(filtered, newAttribs, m);
                tree.addNode(v, subTree);

            }

            return tree;
        }