private static Experiment3Output Experiment3(int neuronCount, decimal minAnnPPV, decimal minAnnNPV, int treeCount, decimal minForestPPV, decimal minForestNPV)
{
var result = new Experiment3Output();
result.NeuronCount = neuronCount;
var metsRecords = LoadDataRecords(TRAINING_DATA_FILE, 0);
DateTime et = DateTime.Now;
var currentMinPPV = 0m;
var currentMinNPV = 0m;
Data data = null;
var learningData = new List<AnnLearningRecord>();
var annPV = new AlgoritamPredictiveValues();
var forestPV = new AlgoritamPredictiveValues();
while (currentMinPPV < minAnnPPV || currentMinNPV < minAnnNPV || currentMinPPV <= currentMinNPV || currentMinPPV < minForestPPV || currentMinNPV < minForestNPV)
{
var es = DateTime.Now;
data = CreateData(metsRecords, 0.8, 0.1);
result.Means = data.Means;
result.StandardDeviations = data.StandardDeviations;
Console.Out.WriteLine("================================");
Console.Out.WriteLine($" ANN PPV, NC:{neuronCount}");
Console.Out.WriteLine("================================");
learningData.Clear();
annPV = Ann(data, neuronCount, learningData, out var ann);
currentMinPPV = annPV.TestPPV;
currentMinNPV = annPV.TestNPV;
result.Ann = ann;
LogAPV(annPV);
LogMessage($"Experiment time: {DateTime.Now - es}, total time {DateTime.Now - et}");
}
var experimentPV = new ExperimentPredictiveValues()
{
AnnPpvLearnNPV = annPV.LearnNPV,
AnnPpvLearnPPV = annPV.LearnPPV,
AnnPpvValidateNPV = annPV.ValidateNPV,
AnnPpvValidatePPV = annPV.ValidatePPV,
AnnPpvTestNPV = annPV.TestNPV,
AnnPpvTestPPV = annPV.TestPPV,
};
using (var tw = File.CreateText($"d:\\mets_experiment_3_{neuronCount}_{DateTime.Now:yyyy_MM_dd_hh_mm}_rndfrst.csv"))
{
var csv = new CsvHelper.CsvWriter(tw);
csv.WriteHeader<AnnLearningRecord>();
csv.NextRecord();
csv.WriteRecords(learningData);
}
using (var tw = File.CreateText($"d:\\mets_experiment_3_PV_{neuronCount}_{DateTime.Now:yyyy_MM_dd_hh_mm}_rndfrst.csv"))
{
var csv = new CsvHelper.CsvWriter(tw);
csv.WriteHeader<ExperimentPredictiveValues>();
csv.NextRecord();
csv.WriteRecords(new ExperimentPredictiveValues[] { experimentPV });
}
return result;
}
private static void Experiment4(Experiment3Output exp3)
{
var metsRecords = LoadDataRecords(TEST_DATA_FILE, 0);
for (int i = 0; i < metsRecords.Count; i++)
{
var mets = CalculateMets(metsRecords[i]);
if (metsRecords[i].METS != mets)
throw new Exception("Invalid data");
}
if (metsRecords.Count > 100)
{
var mr = new List<MetsDataRecord>();
var rnd = new Random();
while (mr.Count < 100)
{
var index = rnd.Next(metsRecords.Count);
mr.Add(metsRecords[index]);
metsRecords.RemoveAt(index);
}
metsRecords = mr;
}
var inputs = CreateInputs(metsRecords).ToArray();
inputs = inputs.ZScores(exp3.Means, exp3.StandardDeviations);
var outputs = CreateOutputs(metsRecords).ToArray();
var annPredictions = new double[inputs.Length][];
for (int i = 0; i < inputs.Length; i++)
{
var annr = exp3.Ann.Compute(inputs[i])[0];
var to = Math.Round(outputs[i][0], 0);
var anno = Math.Round(annr, 0);
annPredictions[i] = new double[] { anno };
}
var annPV = CalculatePredictiveValues(outputs, annPredictions);
var results = new List<Experiment4ResultRecord>();
for (int i = 0; i < metsRecords.Count; i++)
{
results.Add(new Experiment4ResultRecord()
{
AGE = metsRecords[i].AGE,
BMI = metsRecords[i].BMI,
DBP = metsRecords[i].DBP,
FPG = metsRecords[i].FPG,
GEN = metsRecords[i].GEN,
HDL = metsRecords[i].HDL,
HT = metsRecords[i].HT,
METS = metsRecords[i].METS,
METS_PR_ANN = (int)Math.Round(annPredictions[i][0]),
SBP = metsRecords[i].SBP,
TG = metsRecords[i].TG,
WC = metsRecords[i].WC,
WHtR = metsRecords[i].WHtR,
WT = metsRecords[i].WT
});
}
var experimentPV = new Experiment4PredictiveValues()
{
AnnNPV = annPV.NPV,
AnnPPV = annPV.PPV,
};
using (var tw = File.CreateText($"d:\\mets_experiment_4_{exp3.NeuronCount}_{DateTime.Now:yyyy_MM_dd_hh_mm}.csv"))
{
var csv = new CsvHelper.CsvWriter(tw);
csv.WriteHeader<Experiment4ResultRecord>();
csv.NextRecord();
csv.WriteRecords(results);
}
using (var tw = File.CreateText($"d:\\mets_experiment_4_PV_{exp3.NeuronCount}_{DateTime.Now:yyyy_MM_dd_hh_mm}.csv"))
{
var csv = new CsvHelper.CsvWriter(tw);
csv.WriteHeader<Experiment4PredictiveValues>();
csv.NextRecord();
csv.WriteRecords(new Experiment4PredictiveValues[] { experimentPV });
}
}