private string predict(DataRow dataRow, DecisionTreeNode root)
{
if (dataRow == null)
{
throw new ArgumentNullException(nameof(dataRow));
}
if (!IsTrained)
{
throw new InvalidOperationException("DecisionTree cannot predict without being trained");
}
/// If this node is a leaf node, then we have a successful prediction.
if (root.IsLeaf)
{
return(root.ClassLabel);
}
/// Get the split dimension's value and see if first child has that
/// value, if it does, then recurse into the first child to predict.
var value = dataRow.GetValueAtIndex(root.SplitDimensionIndex);
if (root.HasFirstChild(value))
{
return(predict(dataRow, root.FirstChild));
}
/// If the first child's value doesn't match, then see if second child
/// exists. If it does, then recurse into second child to predict.
else if (root.SecondChild != null)
{
return(predict(dataRow, root.SecondChild));
}
/// If the seecond doesn't exist, then predict the most frequest class label.
return(mostFrequentClassLabel);
}
