public static async Task LDAllocation()
{
Storage.Current = new OnlineRepositoryStorage(new DiskStorage("catalyst-models"));
//var train = await Corpus.Reuters.GetAsync();
string connectionStr = "Data Source = (localdb)\\MSSQLLocalDB; Initial Catalog = master; Integrated Security = True; Connect Timeout = 30; Encrypt = False; TrustServerCertificate = False; ApplicationIntent = ReadWrite; MultiSubnetFailover = False";
SqlConnection connection = null;
SqlCommand command = null;
SqlCommand command1 = null;
string sqlQuery = "SELECT * FROM TestApplication.dbo.Files where test = 0";
string sqlQuery1 = "SELECT * FROM TestApplication.dbo.Files where test = 1";
var nlp = Pipeline.For(Language.English);
try
{
connection = new SqlConnection(connectionStr);
command = new SqlCommand(sqlQuery, connection);
command1 = new SqlCommand(sqlQuery1, connection);
connection.Open();
SqlDataReader reader = command.ExecuteReader();
System.Collections.Generic.List <Document> train = new System.Collections.Generic.List <Document>();
System.Collections.Generic.List <Document> test = new System.Collections.Generic.List <Document>();
System.Text.RegularExpressions.Regex reg = new System.Text.RegularExpressions.Regex("/[^/]*/");
while (reader.Read())
{
NLPFile flTrain = new NLPFile((IDataRecord)reader);
//Console.WriteLine(flTrain.FetchData());
var doc = new Document(flTrain.FetchData(), Language.English);
string label = reg.Matches(((string)reader[1]))[2].Value;
label = label.Trim('/');
doc.Labels.Add(label);
train.Add(doc);
var trainDocs = nlp.Process(train).ToArray();
using (var lda = new LDA(Language.English, 0, "reuters-lda"))
{
lda.Data.NumberOfTopics = 20; //Arbitrary number of topics
lda.Train(trainDocs, Environment.ProcessorCount);
await lda.StoreAsync();
}
}
reader.Close();
SqlDataReader reader1 = command1.ExecuteReader();
while (reader1.Read())
{
NLPFile flTest = new NLPFile((IDataRecord)reader1);
//Console.WriteLine(flTest.FetchData());
var doc1 = new Document(flTest.FetchData(), Language.English);
string label = reg.Matches(((string)reader[1]))[2].Value;
label = label.Trim('/');
doc1.Labels.Add(label);
test.Add(doc1);
var testDocs = nlp.Process(test).ToArray();
using (var lda = await LDA.FromStoreAsync(Language.English, 0, "reuters-lda"))
{
foreach (var doc in testDocs)
{
if (lda.TryPredict(doc, out var topics))
{
var docTopics = string.Join("\n", topics.Select(t => lda.TryDescribeTopic(t.TopicID, out var td) ? $"[{t.Score:n3}] => {td.ToString()}" : ""));
Console.WriteLine("------------------------------------------");
Console.WriteLine(doc.Value);
Console.WriteLine("------------------------------------------");
Console.WriteLine(docTopics);
Console.WriteLine("------------------------------------------\n\n");
}
}
}
}
reader1.Close();
}
catch (Exception e)
{
Console.WriteLine("Error: " + e.Message);
}
finally
{
if (command != null || command1 != null)
{
command.Dispose();
command1.Dispose();
}
if (connection != null)
{
connection.Close();
connection.Dispose();
}
}
}
public string FetchData()
{
return(NLPFile.Process(fileName));
}
