public DictionaryInput(string name)
{
InitializeComponent();
DropDownStyle = ComboBoxStyle.DropDownList;
InputName = name;
DictionaryName = name.Substring(0, name.Length - 2);
using (var db = new GlobalTerrorismContext())
{
var type = typeof(ISystemDictionary).Assembly.GetType($"BIAI.Data.Model.{DictionaryName}");
var tableName = typeof(GlobalTerrorismContext).GetProperties().Single(x => CheckForDbSet(x, type)).Name;
foreach (var entry in db.Set(type).SqlQuery($"SELECT * FROM {tableName}").Cast <ISystemDictionary>())
{
var ind = Items.Add(entry.Name);
dictionaryMapping.Add(ind, entry.Id);
}
}
}
public void Start()
{
var dataSets = new List <TrainingDataSet>();
trainingLogger.Message($"{BELT}{DateTime.Now.TimeOfDay}{BELT}");
trainingLogger.Message("Opening connection to database");
using (var db = new GlobalTerrorismContext())
{
var sampleRecord = db.AttackRecords.First(); // assert database connection
trainingLogger.Message("Preparing");
var count = db.AttackRecords.Count();
var nulls = 0;
initializers = Columns.Select(x => new InputInitializer(x.PropertyInfo)).ToList();
trainingLogger.Message("Downloading data");
var attackRecords = db.AttackRecords.ToList();
trainingLogger.Message("Normalizing data");
for (int i = 0; i < count; i++)
{
foreach (var initializer in initializers)
{
initializer.UpdateLimits(attackRecords[i]);
}
//log.Progress($"Normalizing data: {(float)i / count * 100}%");
}
trainingLogger.Message("Creating data sets");
//log.Finish();
for (int i = 0; i < count; i++)
{
var inputs = initializers.Select(x => x.TryGetValue(attackRecords[i]));
if (inputs.Any(x => x == null))
{
nulls++;
continue;
}
var dataSet = new TrainingDataSet
{
Inputs = inputs.Select(x => x.Value).ToArray(),
Outputs = CreateOutput(attackRecords[i].Fatalities)
};
//log.Progress($"Creating data sets: {(float)i / count * 100}%");
dataSets.Add(dataSet);
}
//log.Finish();
trainingLogger.Message($"{nulls} records skipped as they contains nulls.");
}
trainingLogger.Message("Training started");
network.Train(
trainingDataSets: dataSets,
learningRate: learningRate,
learningDataPercentage: learningDataRatio
);
trainingLogger.Message("Finished");
trainingLogger.Message($"Training accuracy: {network.Accuracy}");
TrainingCompleted?.Invoke(this, ProcessResult.Success);
}
