public void obnaryjenieAnomaliiPCAP(object a)
{
InfaDlyaObnaryjeniyaAnomaliiPCAP infa = (InfaDlyaObnaryjeniyaAnomaliiPCAP)a;
List <List <Double> > testData = infa.data; //обучающие данные
int koli4estvoNaOby4enie = Convert.ToInt32(testData.Count / 100 * infa.dolyaNaOby4enie);
List <List <Double> > trainData = new List <List <double> >(koli4estvoNaOby4enie);
for (int i = 0; i < koli4estvoNaOby4enie; i++)
{
trainData.Add(testData[infa.nomerDoli * koli4estvoNaOby4enie + i]);
}
/*
* Calling isolationForestAlgorithm with input data, number of trees which is roughly taken to be
* 20% of number of data points and sub sampling size which is taken as 10% of number of data points.
* (входные (обучающие) данные, количество деревьев, размер подвыборки для ДР)
*/
isolationForestAlgorithm isolationForestAlgorithm = new isolationForestAlgorithm();
label1.Invoke((Action)(() => { label1.Text = "Обучение леса..."; }));
//Можно поиграть с параметрами
List <Tree> forest = isolationForestAlgorithm.buildForest(trainData, 100, koli4estvoNaOby4enie); //(data, data.size() / 5, data.size() / 10); //оригинал
/*
* Calculating anomalyScore for each data point in input data. This is calculated for each data point
* by calculating the average of the path length for each point.
*/
anomalyScore anomalyScore = new anomalyScore();
for (int i = 0; i < testData.Count; i++)
{
double score = anomalyScore.Calculating(forest, testData[i], testData.Count); //Оценка аномалии
int flagAnomalii;
if (score > infa.porogOcenki)
{
flagAnomalii = 1;
}
else
{
flagAnomalii = 0;
}
dataGridView2.Invoke((Action)(() =>
{
dataGridView2.Rows[i].Cells[4].Value = score;
dataGridView2.Rows[i].Cells[5].Value = flagAnomalii;
})); //Добавление строки в таблицу
label1.Invoke((Action)(() => { label1.Text = "Обработано данных:" + i + "/" + testData.Count; }));
progressBar1.Invoke((Action)(() => { progressBar1.Value = i; }));
}
}
public void obnaryjenieAnomaliiARFF(object a)
{
InfaDlyaObnaryjeniyaAnomaliiARFF infa = (InfaDlyaObnaryjeniyaAnomaliiARFF)a;
List <List <Double> > dataTrain = infa.dataTrain; //обучающие данные
List <List <Double> > dataTest = infa.dataTest; //обучающие данные
DateTime dateTime; //время
/*
* Calling isolationForestAlgorithm with input data, number of trees which is roughly taken to be
* 20% of number of data points and sub sampling size which is taken as 10% of number of data points.
* (входные (обучающие) данные, количество деревьев, размер подвыборки для ДР)
*/
isolationForestAlgorithm isolationForestAlgorithm = new isolationForestAlgorithm();
label1.Invoke((Action)(() => { label1.Text = "Обучение леса..."; }));
dateTime = DateTime.Now;
//Можно поиграть с параметрами
List <Tree> forest = isolationForestAlgorithm.buildForest(dataTrain, 100, Convert.ToInt32(dataTrain.Count * 0.66)); //(data, data.size() / 5, data.size() / 10); //оригинал
textBoxLog.Invoke((Action)(() =>
{
textBoxLog.Text += "Количество элементов на обучение" + dataTrain.Count;
textBoxLog.Text += "Время обучения" + (DateTime.Now - dateTime);
})); //Вывод времени обучения
/*
* Calculating anomalyScore for each data point in input data. This is calculated for each data point
* by calculating the average of the path length for each point.
*/
anomalyScore anomalyScore = new anomalyScore();
dataGridView6.Invoke((Action)(() =>
{
dataGridView6.Columns.Add("columns6_Score", "Оценка аномалии");
//dataGridView6.Columns.Add("columns6_flagAnomalii", "Флаг аномалии");
})); //Добавление строки в таблицу
int countDataTest = dataTest.Count;
ocenkaAnomalii = new double[countDataTest];
dateTime = DateTime.Now;
for (int i = 0; i < countDataTest; i++)
{
ocenkaAnomalii[i] = anomalyScore.Calculating(forest, dataTest[i], countDataTest); //Оценка аномалии
dataGridView6.Invoke((Action)(() =>
{
dataGridView6.Rows[i].Cells[dataGridView6.Columns.Count - 1].Value = ocenkaAnomalii[i];
})); //Добавление строки в таблицу
label1.Invoke((Action)(() => { label1.Text = "Обработано данных:" + i + "/" + countDataTest; }));
progressBar1.Invoke((Action)(() => { progressBar1.Value = i; }));
}
textBoxLog.Invoke((Action)(() =>
{
textBoxLog.Text += "Количесвто элементов на тестирование" + countDataTest;
textBoxLog.Text += "Время тестирования" + (DateTime.Now - dateTime);
})); //Вывод времени тестирования
}