public C45AlgorithmDataOptimized(TableFixedData data, TreeOptions options)
{
_data = data;
if (options == null)
{
options = new TreeOptions();
}
_options = options;
}
public Forest BuildForest(TableFixedData data, TreeOptions options = null, int[] attributes = null)
{
if (options == null)
{
options = new TreeOptions();
}
var countOfItemsInTree = Convert.ToInt32(_sampleRatio * data.Count);
var countOfVariablesInTree =
Convert.ToInt32(_coverageRatio.HasValue
? Math.Floor(_coverageRatio.Value * (data.Attributes.Length - 1))
: Math.Ceiling(Math.Sqrt(data.Attributes.Length - 1)));
var rows = Enumerable.Range(0, data.Count).ToArray();
if (attributes == null)
{
attributes = new int[data.Attributes.Length - 1];
var currentIndex = 0;
for (int index = 0; index < data.Attributes.Length; index++)
{
if (data.IsClassAttribute(index))
{
continue;
}
attributes[currentIndex++] = index;
}
}
var sampleRows = new int[countOfItemsInTree];
var sampleAttributes = new int[countOfVariablesInTree];
var c45Algorithm = new C45AlgorithmDataOptimized(data, options);
var ret = new Forest(data.ClassesValue.Length);
for (int i = 0; i < _trees; i++)
{
rows.Sample(sampleRows);
attributes.Sample(sampleAttributes);
var tree = c45Algorithm.BuildConditionalTree(sampleRows, sampleAttributes);
ret.Add(tree);
}
return(ret);
}