//[ValidateAntiForgeryToken]
public IActionResult Recommendations(float supportPercentage, int confidence, DateTime startDate, DateTime endDate)
{
IEnumerable <SequenceSupport> sequenceSupports = ReadFrequentSequences();
//List<FrequentSequentialRule> frequentSequentialRules = FindFrequentSequentialRules(sequenceSupports);
List <UserSequence> userSequences = CreateUserSequences(startDate, endDate);
int userCount = userSequences.Count();
int support = Convert.ToInt32(Math.Floor((supportPercentage / 100) * userCount));
IList <SequenceSupport> sequenceSupports2Items = sequenceSupports.
Where(a => a.sequence.Count == 2 && a.sequence[0].Count == 1 && a.sequence[1].Count == 1 && a.support >= support).ToList();
IList <SequenceSupport> sequenceSupports1Items = sequenceSupports.
Where(a => a.sequence.Count == 1 && a.sequence[0].Count == 1 && a.support >= support).ToList();
IList <SequenceSupport> sequenceSupports2ItemsRules = new List <SequenceSupport>();
foreach (SequenceSupport sequenceSupport in sequenceSupports2Items)
{
int ancestorSupport = sequenceSupports1Items.Single(a => a.sequence[0][0] == sequenceSupport.sequence[0][0]).support;
if (((float)sequenceSupport.support / (float)ancestorSupport) >= ((float)confidence / 100.0))
{
sequenceSupports2ItemsRules.Add(sequenceSupport);
}
}
SpmRecommendation sequentialRecommendation = new SpmRecommendation();
System.Diagnostics.Debug.WriteLine("Step 0 - Read Data: " + DateTime.Now.TimeOfDay + " - Read data");
List <RecommendedItems> recommendedItemsList = sequentialRecommendation.Recommend(sequenceSupports2ItemsRules, userSequences, 50);
SavetoDatabase(recommendedItemsList);
System.Diagnostics.Debug.WriteLine("Step 5: " + DateTime.Now.TimeOfDay + " - Save results");
return(View(recommendedItemsList));
}
//[ValidateAntiForgeryToken]
public IActionResult OptimumSupportConfidence(float supportFrom, float supportTo, float supportSteps,
float confidenceFrom, float confidenceTo, float confidenceSteps,
DateTime trainStartDate, DateTime trainEndDate, DateTime testStartDate, DateTime testEndDate)
{
List <SupportConfidenceAccuracyNrec> SupportConfidenceAccuracyNrecs = new List <SupportConfidenceAccuracyNrec>();
//Select purchases in test period
IList <UserItemPurchase> purchasesAllTest = _dbContext.UkRetailOriginalSales
.Where(a => a.InvoiceDate.Date >= testStartDate.Date && a.InvoiceDate.Date <= testEndDate.Date &&
a.CustomerID != null && a.CustomerID < 13000 && a.Quantity > 0 &&
string.Compare(a.StockCode, "a") == -1)
.Select(a => new UserItemPurchase {
User = (Int32)a.CustomerID, Item = a.StockCode
}).ToList();
//Select purchases in train period
IList <int> purchasesAllTrain = _dbContext.UkRetailOriginalSales
.Where(a => a.InvoiceDate.Date >= trainStartDate.Date && a.InvoiceDate.Date <= trainEndDate.Date &&
a.CustomerID != null && a.CustomerID < 13000 && a.Quantity > 0 &&
string.Compare(a.StockCode, "a") == -1).Select(a => (Int32)a.CustomerID).Distinct().ToList();
//Select users which the user bought something both in test period and train priod
List <int> purchaseUsers = purchasesAllTest.Select(a => a.User).Where(a => purchasesAllTrain.Contains(a)).Distinct().ToList();
//Select purchass where user has bought something both in training and testing
IList <UserItemPurchase> purchases = purchasesAllTest.Where(a => purchaseUsers.Contains(a.User)).ToList();
IEnumerable <SequenceSupport> sequenceSupports = ReadFrequentSequences();
//List<FrequentSequentialRule> frequentSequentialRules = FindFrequentSequentialRules(sequenceSupports);
List <UserSequence> userSequences = CreateUserSequences(trainStartDate, trainEndDate);
int userCount = userSequences.Count();
//Parallel.ForEach(counter, new ParallelOptions { MaxDegreeOfParallelism = Environment.ProcessorCount - 1 }, supportPercentage =>
for (float supportPercentage = supportFrom; supportPercentage <= supportTo; supportPercentage += supportSteps)
{
var counter = new List <float>();
for (float i = confidenceFrom; i <= confidenceTo; i += confidenceSteps)
{
counter.Add(i);
}
Parallel.ForEach(counter, new ParallelOptions {
MaxDegreeOfParallelism = Environment.ProcessorCount
}, confidence =>
//for (float confidence = confidenceFrom; confidence <= confidenceTo; confidence += confidenceSteps)
{
//=========================================================
//Recommend Items
//=========================================================
int support = Convert.ToInt32(Math.Floor((supportPercentage / 100) * userCount));
IList <SequenceSupport> sequenceSupports2Items = sequenceSupports.
Where(a => a.sequence.Count == 2 && a.sequence[0].Count == 1 && a.sequence[1].Count == 1 && a.support >= support).ToList();
IList <SequenceSupport> sequenceSupports1Items = sequenceSupports.
Where(a => a.sequence.Count == 1 && a.sequence[0].Count == 1 && a.support >= support).ToList();
IList <SequenceSupport> sequenceSupports2ItemsRules = new List <SequenceSupport>();
foreach (SequenceSupport sequenceSupport in sequenceSupports2Items)
{
int ancestorSupport = sequenceSupports1Items.Single(a => a.sequence[0][0] == sequenceSupport.sequence[0][0]).support;
if (((float)sequenceSupport.support / (float)ancestorSupport) >= ((float)confidence / 100.0))
{
sequenceSupports2ItemsRules.Add(sequenceSupport);
}
}
SpmRecommendation sequentialRecommendation = new SpmRecommendation();
List <RecommendedItems> recommendedItemsList = sequentialRecommendation.Recommend(sequenceSupports2ItemsRules, userSequences, 50);
System.Diagnostics.Debug.WriteLine("Step 0 - Recomendation finished: " + DateTime.Now.TimeOfDay + " - Support: " + supportPercentage + " - Confidence: " + confidence);
//=========================================================
//Evaluate recomendations
//=========================================================
//Select recomendations which user has purchased both in training and testing
List <RecommendedItems> recommendations = recommendedItemsList.Where(a => purchaseUsers.Contains(a.User)).ToList();
AccuracyNrec accuracyNrec = CalculateAccuracy(recommendations, purchases);
SupportConfidenceAccuracyNrec supportConfidenceAccuracyNrec = new SupportConfidenceAccuracyNrec();
supportConfidenceAccuracyNrec.Support = supportPercentage;
supportConfidenceAccuracyNrec.Confidence = confidence;
supportConfidenceAccuracyNrec.AccuracyNrec = accuracyNrec;
SupportConfidenceAccuracyNrecs.Add(supportConfidenceAccuracyNrec);
System.Diagnostics.Debug.WriteLine("Step 0 - Evaluation finished: " + DateTime.Now.TimeOfDay + " - Support: " + supportPercentage + " - Confidence: " + confidence);
});
}
return(View(SupportConfidenceAccuracyNrecs));
}