private static void TrainingRecordData()
{
var mongoClient = new MongoClient("mongodb://*****:*****@"[^a-zA-Z]", " ").Trim().ToLowerInvariant().Split(new[] { ' ' }, StringSplitOptions.RemoveEmptyEntries).Where(d => d.Count() < 20).ToArray();
var trainingDataCollection = database.GetCollection <ProcessInfoLabeledItem>("training_data");
var records = trainingDataCollection.Find(Builders <ProcessInfoLabeledItem> .Filter.Empty).ToList();
var vocabulary = records.Select(c => c.Title + " " + c.Process).SelectMany(filter).Distinct().OrderBy(str => str).ToList();
List <string> x = records.Select(item => item.Title + " " + item.Process).ToList();
double[] y = records.Select(item => (double)item.Category).ToArray();
var problemBuilder = new TextClassificationProblemBuilder();
problemBuilder.RefineText = filter;
var problem = problemBuilder.CreateProblem(x, y, vocabulary.ToList());
const int C = 1;
var model = new C_SVC(problem, KernelHelper.LinearKernel(), C);
var _predictionDictionary = new Dictionary <Karma, string> {
{ Karma.Bad, "Bad" }, { Karma.Good, "Good" }, { Karma.Neutral, "Neutral" }
};
var newXs = database.GetCollection <AppUsageRecord>("daily_records").Find(Builders <AppUsageRecord> .Filter.Eq(f => f.Id, AppUsageRecord.GetGeneratedId(DateTime.Now))).FirstOrDefault().ActiveApps.Select(c => c.Value).Select(c => c.MainWindowTitle + " " + c.ProcessName);
foreach (var _x in newXs)
{
var newX = TextClassificationProblemBuilder.CreateNode(_x, vocabulary, problemBuilder.RefineText);
var predictedY = model.Predict(newX);
Console.WriteLine($"For title {_x}");
Console.WriteLine($"The prediction is {_predictionDictionary[(Karma)predictedY]}");
}
}
private void TrainingData()
{
string dateFilePath = Path.Combine(Directory.GetCurrentDirectory(), $"sunnyData.csv");
var dataTable = DataTable.New.ReadCsv(dateFilePath);
List <string> x = dataTable.Rows.Select(row => row["Text"]).ToList();
double[] y = dataTable.Rows.Select(row => double.Parse(row["IsSunny"])).ToArray();
var vocabulary = x.SelectMany(GetWords).Distinct().OrderBy(w => w).ToList();
var problemBuilder = new TextClassificationProblemBuilder();
var problem = problemBuilder.CreateProblem(x, y, vocabulary.ToList());
const int C = 1;
var model = new C_SVC(problem, KernelHelper.LinearKernel(), C);
string userInput;
var _predictionDictionary = new Dictionary <int, string> {
{ -1, "Rainy" }, { 1, "Sunny" }
};
do
{
userInput = Console.ReadLine();
var newX = TextClassificationProblemBuilder.CreateNode(userInput, vocabulary);
var predictedY = model.Predict(newX);
Console.WriteLine("The prediction is {0}", _predictionDictionary[(int)predictedY]);
Console.WriteLine(new string('=', 50));
} while (userInput != "quit");
Console.WriteLine("");
}