private static void dbSQLite()
{
// Connect to the database
var path = Path.GetFullPath("./database.sqlite");
var db = new SqliteDb(path);
db.Connect();
// Populate a list of iris from the database
List <Iris> listPredict = new List <Iris>();
db.Command <Iris>("SELECT * FROM Iris", (iris) =>
{
listPredict.Add(iris);
});
// Perform the clustering data mining operation based on attribute(s)
var clusterer = new Clustering <Iris>(5, listPredict);
clusterer.BuildModel("SepalLengthCm");
// For each item, predict and output which cluster it's in
foreach (var item in listPredict)
{
// Each item is tested against the test data set
var result = clusterer.Evaluate(item);
Console.WriteLine(result.SelectedClusterId);
Console.WriteLine(string.Join(" ", result.Distance));
}
}
static void Main(string[] args)
{
// Choose the data mining operation from input
Console.WriteLine("Input BC for binary classification, MC for multiclass classification, or C for clustering");
var userInput = Console.ReadLine();
if (userInput == "BC")
{
Console.WriteLine("BC selected");
// Connect to the binary classification DB
var path = Path.GetFullPath("./binaryclassification.db");
var db = new SqliteDb(path);
db.Connect();
// Setup a tokenizer, parser, and SQL converter
var handler = new FUSQLHandler();
var query = handler.ParseQuery("CHECK 'PRETTY GOOD!' FROM imdblabelled\n");
var translation = Translator.TranslateQuery <Text>(query);
var result = translation.RunBinaryClassification(db);
Console.WriteLine($"Sentiment: {translation.Operation.Text} | Prediction: {(Convert.ToBoolean(result.Prediction) ? "Positive" : "Negative")} | Probability: {result.Probability} ");
Console.ReadLine();
}
else if (userInput == "MC")
{
Console.WriteLine("MC selected");
// Connect to the multiclass classification DB
var path = Path.GetFullPath("./multiclass.db");
var db = new SqliteDb(path);
db.Connect();
// Setup a tokenizer, parser, and SQL converter
var handler = new FUSQLHandler();
var query = handler.ParseQuery("IDENTIFY '404 error not found' 'Cant find webpage!' FROM issuestrain\n");
var translation = Translator.TranslateQuery <IssueDesc>(query);
var result = translation.RunMulticlassClassification(db);
//var resultView = new MulticlassClassification();
//resultView.BuildModel();
//MulticlassClassificationData issue = new MulticlassClassificationData()
//{
// Title = "WebSockets communication is slow in my machine",
// Description = "The WebSockets communication used under the covers by SignalR looks like is going slow in my development machine.."
//};
Console.WriteLine($"=============== Single Prediction just-trained-model - Result: {result.Area} ===============");
Console.ReadLine();
}
else if (userInput == "C")
{
Console.WriteLine("C selected");
// Connect to the database
var path = Path.GetFullPath("./database.sqlite");
var db = new SqliteDb(path);
db.Connect();
// Setup a tokenizer, parser, and SQL converter
var handler = new FUSQLHandler();
var query = handler.ParseQuery("FIND 5 GROUPS irisClusters USING SepalLengthCm PetalLengthCm FROM Iris\n");
var translation = Translator.TranslateQuery <Iris>(query);
var resultView = translation.RunClustering(db);
// Perform a data mining query operation
// dbSQLite();
foreach (var key in (resultView as ClusterResultView <Iris>).Clusters.Keys)
{
Console.WriteLine("Cluster " + key + " count : " + (resultView as ClusterResultView <Iris>).Clusters[key].Count);
}
Console.ReadLine();
}
else
{
Console.WriteLine("\nInvalid input.");
}
}
