public void TestWithDataYouveNeverSeen_StillWorks()
{
DecisionTreeLevel decisionTree = new DecisionTreeLevel(0);
decisionTree.D3(_generic3BooleanAttributes,
new List <DataSetValue>()
{
new DataSetValue(new List <string>()
{
"0", "0", "0"
}, false),
new DataSetValue(new List <string>()
{
"0", "0", "1"
}, true),
new DataSetValue(new List <string>()
{
"0", "1", "0"
}, false),
new DataSetValue(new List <string>()
{
"0", "1", "1"
}, false),
new DataSetValue(new List <string>()
{
"1", "0", "0"
}, false),
new DataSetValue(new List <string>()
{
"1", "0", "1"
}, false),
new DataSetValue(new List <string>()
{
"1", "1", "0"
}, false),
new DataSetValue(new List <string>()
{
"1", "1", "1"
}, false),
});
decisionTree.Evaluate(new List <string>()
{
"0", "0", "JORGE"
}).Should().BeFalse();
}
private void VerifyDecisionTreeCanLearnTable(List <DataSetValue> tableToLearn)
{
DecisionTreeLevel decisionTree = new DecisionTreeLevel(0);
decisionTree.D3(_generic3BooleanAttributes, tableToLearn);
decisionTree.TrimTree();
// The tree should have learnt every value
foreach (var dataSetValue in tableToLearn)
{
decisionTree.Evaluate(dataSetValue.Values).Should().Be(dataSetValue.Output);
}
// Break here to visualize decision tree
string visualizedDecisionTree = decisionTree.SerializeDecisionTree();
Debug.WriteLine("Visualized decision tree:\n" + visualizedDecisionTree);
}
