public void BuildTree(string fileName, string outputDirectory = "Output")
{
var data = LoadDataFromfCSV(fileName);
var decisionTreeName = Path.GetFileNameWithoutExtension(fileName);
var algorithm = new C45Algorithm();
var fixedData = TableFixedData.FromTableData(data);
if (!Directory.Exists(outputDirectory))
{
Directory.CreateDirectory(outputDirectory);
}
var decisionalTree = algorithm.BuildConditionalTree(fixedData, new TreeOptions());
var decisionTreeRenderer = new DecisionTreeRenderer();
var bitmap = decisionTreeRenderer.RenderTree(decisionalTree, new Size(100, 50));
var decisionTreeFileName = Path.Combine(outputDirectory, string.Format("{0}.jpg", decisionTreeName));
bitmap.Save(decisionTreeFileName, ImageFormat.Jpeg);
var img = new BitmapImage(new Uri(decisionTreeFileName, UriKind.RelativeOrAbsolute));
img.Freeze();
//img.EndInit();
//mainGrid.Children.Remove(tree);
tree.Source = img;
tree.UpdateLayout();
//tree = new Image {Source = img};
//mainGrid.Children.Add(tree);
//Grid.SetRow(tree,1);
//Grid.SetColumn(tree, 1);
txtMessage.Text = decisionalTree.ToPseudocode();
}
public static void TestC45()
{
var data = LoadDataFromfCSV("Data2.csv");
var algorithm = new C45Algorithm();
var fixedData = TableFixedData.FromTableData(data);
var decisionalTree = algorithm.BuildConditionalTree(fixedData, new TreeOptions());
var decisionTreeRenderer = new DecisionTreeRenderer();
var bitmap = decisionTreeRenderer.RenderTree(decisionalTree, new Size(100, 50));
bitmap.Save("test.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);
var pseudocode = decisionalTree.ToPseudocode();
using (var textString = new StreamReader(@"C:\Research\Kaggle\Expedia\trainData\train.csv"))
{
while (!textString.EndOfStream)
{
var line = textString.ReadLine();
}
}
}
public static void TestC45()
{
var data = LoadDataFromfCSV("Data2.csv");
var algorithm = new C45Algorithm();
var fixedData = TableFixedData.FromTableData(data);
var decisionalTree = algorithm.BuildConditionalTree(fixedData, new TreeOptions());
var decisionTreeRenderer = new DecisionTreeRenderer();
var bitmap = decisionTreeRenderer.RenderTree(decisionalTree, new Size(100, 50));
bitmap.Save("test.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);
var pseudocode = decisionalTree.ToPseudocode();
using (var textString = new StreamReader(@"C:\Research\Kaggle\Expedia\trainData\train.csv"))
{
while (!textString.EndOfStream)
{
var line = textString.ReadLine();
}
}
}
public void BuildTree(string fileName, string outputDirectory = "Output")
{
var data = LoadDataFromfCSV(fileName);
var decisionTreeName = Path.GetFileNameWithoutExtension(fileName);
var algorithm = new C45Algorithm();
var fixedData = TableFixedData.FromTableData(data);
if (!Directory.Exists(outputDirectory))
{
Directory.CreateDirectory(outputDirectory);
}
var decisionalTree = algorithm.BuildConditionalTree(fixedData, new TreeOptions());
var decisionTreeRenderer = new DecisionTreeRenderer();
var bitmap = decisionTreeRenderer.RenderTree(decisionalTree, new Size(100, 50));
var decisionTreeFileName = Path.Combine(outputDirectory, string.Format("{0}.jpg", decisionTreeName));
bitmap.Save(decisionTreeFileName, ImageFormat.Jpeg);
var img = new BitmapImage(new Uri(decisionTreeFileName, UriKind.RelativeOrAbsolute));
img.Freeze();
//img.EndInit();
//mainGrid.Children.Remove(tree);
tree.Source = img;
tree.UpdateLayout();
//tree = new Image {Source = img};
//mainGrid.Children.Add(tree);
//Grid.SetRow(tree,1);
//Grid.SetColumn(tree, 1);
txtMessage.Text = decisionalTree.ToPseudocode();
}
