예제 #1
0
        /// <summary>
        /// Private method that tests a fold
        /// </summary>
        /// <param name="foldDirectories">directory in which the folds are placed</param>
        /// <param name="fold">the current fold being tested</param>
        /// <returns>the classifier containing accuracy, precision and recall</returns>
        private SVMClassify TestFold(string[] foldDirectories, int fold)
        {
            SVMClassify classifier = new SVMClassify();

            classifier.ExecuteClassifier("svm_classify.exe", Path.Combine(foldDirectories[fold], fold + ".data"),
                                         Path.Combine(foldDirectories[fold], fold + ".model"), Path.Combine(foldDirectories[fold], fold + ".output"),
                                         Path.Combine(foldDirectories[fold], fold + ".test.log.txt"), Path.Combine(foldDirectories[fold], fold + ".incorrect.txt"),
                                         false);

            return(classifier);
        }
예제 #2
0
        /// <summary>
        /// Perform n-fold cross validation
        /// </summary>
        /// <param name="cvFolder">folder that contains the folds</param>
        /// <param name="silent">whether or not to be silent on the screen</param>
        /// <param name="learner">The svm learner with the relevant parameters</param>
        /// <returns>results</returns>
        public Results PerformCrossValidation(String cvFolder, bool silent, SVMLearn learner)
        {
            String[] foldDirectories = Directory.GetDirectories(cvFolder);
            double[] precisions      = new double[foldDirectories.Length];
            double[] recalls         = new double[foldDirectories.Length];
            double[] accuracies      = new double[foldDirectories.Length];

            for (int counter = 0; counter < foldDirectories.Length; counter++)
            {
                String concatenatedFile = Path.Combine(foldDirectories[counter], "combined" + counter + ".data");

                using (StreamWriter writer = new StreamWriter(concatenatedFile, false))
                {
                    for (int innerCounter = 0; innerCounter < foldDirectories.Length; innerCounter++)
                    {
                        if (innerCounter != counter)
                        {
                            using (StreamReader reader =
                                       new StreamReader(Path.Combine(foldDirectories[innerCounter], innerCounter + ".data")))
                            {
                                while (!reader.EndOfStream)
                                {
                                    writer.WriteLine(reader.ReadLine());
                                }
                            }
                        }
                    }
                }

                //concatenated file created. now train and test. delete concatenated file

                this.TrainFold(foldDirectories, counter, concatenatedFile, silent, learner);
                File.Delete(concatenatedFile);
                SVMClassify classifier = this.TestFold(foldDirectories, counter);

                precisions[counter] = classifier.Precision;
                recalls[counter]    = classifier.Recall;
                accuracies[counter] = classifier.Accuracy;
            }

            double accuracy  = accuracies.Average(),
                   precision = precisions.Average(),
                   recall    = recalls.Average();

            Console.WriteLine("Accuracy: {0}, Precision: {1}, Recall: {2}", accuracy, precision, recall);

            return(new Results
            {
                accuracy = accuracy,
                precision = precision,
                recall = recall
            });
        }
예제 #3
0
파일: Utilities.cs 프로젝트: wushian/MLEA
        /// <summary>
        /// Private method that tests a fold
        /// </summary>
        /// <param name="foldDirectories">directory in which the folds are placed</param>
        /// <param name="fold">the current fold being tested</param>
        /// <returns>the classifier containing accuracy, precision and recall</returns>
        private SVMClassify TestFold(string[] foldDirectories, int fold)
        {
            SVMClassify classifier = new SVMClassify();
            classifier.ExecuteClassifier("svm_classify.exe", Path.Combine(foldDirectories[fold], fold + ".data"),
                Path.Combine(foldDirectories[fold], fold + ".model"), Path.Combine(foldDirectories[fold], fold + ".output"),
                Path.Combine(foldDirectories[fold], fold + ".test.log.txt"), Path.Combine(foldDirectories[fold], fold + ".incorrect.txt"),
                false);

            return classifier;
        }