Potential bug in RandomForest or C45Learning #249
Description
Hi,
I am getting an IndexOutOfBoundsException in line 640 of C45Learning in the current 3.1.0-alpha release, when executing the following code (I am aware of the "insert code" feature, but it doesn't seem to work with the following code...so sorry for the bad formatting):
using System;
using System.Collections.Generic;
using System.Globalization;
using System.IO;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using Accord.MachineLearning;
using Accord.MachineLearning.DecisionTrees;
using Accord.MachineLearning.DecisionTrees.Learning;
using Accord.MachineLearning.VectorMachines;
using Accord.MachineLearning.VectorMachines.Learning;
using Accord.Statistics.Kernels;
using CsvHelper;
using Microsoft.VisualBasic.FileIO;
namespace YuriMLClass
{
class Program
{
static void Main(string[] args)
{
CultureInfo.DefaultThreadCurrentCulture = CultureInfo.InvariantCulture;
var times = ReadCSV("ALL.times");
var features = ReadCSV("ALL.features");
var didSolve = times.Select(list => list.Select(d => d < 5000).ToList()).ToList();
var foldCount = 10;
for (int i = 0; i < foldCount; i++)
{
var elementsPerFold = didSolve.Count / foldCount;
var y_test = didSolve.Skip(i * elementsPerFold).Take(elementsPerFold);
var y_train = didSolve.Except(y_test).ToList();
var x_test = features.Skip(i * elementsPerFold).Take(elementsPerFold);
var x_train = features.Except(x_test);
var allSolverPredictions = new List<bool[]>();
for (int j = 0; j < y_train.First().Count; j++)
{
var y_train_current_solver = y_train.Select(list => list.Skip(j).First()).Select(b => b ? 1 : 0);
var randomForestLearning = new RandomForestLearning() { Trees = 10 };
var currentSolverPredictions = new List<bool>();
var randomForest = randomForestLearning.Learn(x_train.Select(list => list.ToArray()).ToArray(),
y_train_current_solver.ToArray());
foreach (var test_instance in x_test)
{
var compute = randomForest.Compute(test_instance.ToArray());
currentSolverPredictions.Add(compute != 0);
}
allSolverPredictions.Add(currentSolverPredictions.ToArray());
}
}
}
private static List<List<double>> ReadCSV(string filename)
{
var returnList = new List<List<double>>();
using (var parser = new TextFieldParser(filename))
{
parser.TextFieldType = FieldType.Delimited;
parser.SetDelimiters(",");
int i = 0;
while (!parser.EndOfData)
{
var fields = parser.ReadFields();
if (i == 0)
{
i++;
continue;
}
//Process row
var timeValues = fields.Skip(1).Select(double.Parse).ToList();
returnList.Add(timeValues);
}
}
return returnList;
}
}
}