public bool ApplicantTest() { try { const string fileBase = "D:/Users/Documentos/Desktop/bank-additional/bank-analiser.csv"; const string fileLearning = "D:/Users/Documentos/Desktop/bank-additional/bank-analiser-learning.csv"; ///this is data test.... var candidato = new Model.ApplicantDataCluster { age = 25, consconfid = -31, education = 1, empratevar = 1, housing = 0, loan = 1, duration = 300 }; var result = new Clusterizing().GetClusterizing(fileBase, fileLearning, candidato); return(result != null); } catch { return(false); } }
public ActionResult Create([Bind(Include = "Id,Education,Age,Housing,Loan,Duration,EmpRateVar,ConsConfId,SearchData,DeservCredit,Cpf,BornDate,Name")] Applicant applicant) { const string fileBase = "D:/Users/Documentos/Desktop/bank-additional/bank-analiser.csv"; const string fileLearning = "D:/Users/Documentos/Desktop/bank-additional/bank-analiser-learning.csv"; if (ModelState.IsValid) { var applcant = new ApplicantDataCluster { age = applicant.Age, consconfid = -(applicant.ConsConfId + 400 / 10), duration = (applicant.Duration * 10) + 500, education = applicant.Education, empratevar = applicant.EmpRateVar, housing = applicant.Housing, loan = applicant.Loan }; var analiseResult = new Clusterizing().GetClusterizing(fileBase, fileLearning, applcant); return(RedirectToAction("Index", "AnaliseResult", new { group1 = analiseResult.Distances[0], group2 = analiseResult.Distances[1], resultGroup = analiseResult.PredictedClusterId })); } else { return(RedirectToAction("index", "AnaliseResult", new { group1 = 0, group2 = 0, resultGroup = 1 })); } }
// GET: DataAnalise public void Index() { const string fileBase = "bank-analiser.csv"; const string fileLearning = "bank-analiser-learning.csv"; var dataAnaliser = new Clusterizing(); dataAnaliser.GetClusterizing(fileBase, fileLearning); }
public ActionResult Input(string Count, string method, string create) { int c; int[] clustering; Clusterizing cluster = new Clusterizing(); c = int.Parse(Count); cluster.InitializeTuples(c, create); if (method == "k-means") { clustering = cluster.Cluster(); } else if (method == "Forel") { clustering = cluster.Cluster2(); } return(View()); }
public ActionResult Contact(string Vertex, string method, string create) { int c; int[] clustering = { }; Clusterizing cluster = new Clusterizing(); if (Vertex.Length != 0) { c = int.Parse(Vertex); cluster.InitializeTuples(c, create); if (method == "k-means") { clustering = cluster.Cluster(); } else if (method == "Forel") { clustering = cluster.Cluster2(); } ViewBag.Mass = clustering; } return(View("Contact")); }