static void Main(string[] args)
{
Assembly assembly = Assembly.GetExecutingAssembly();
Assembly.LoadFile(Path.GetDirectoryName(assembly.Location) + Path.DirectorySeparatorChar + "MyMediaLiteExperimental.dll");
AppDomain.CurrentDomain.UnhandledException += new UnhandledExceptionEventHandler(Handlers.UnhandledExceptionHandler);
Console.CancelKeyPress += new ConsoleCancelEventHandler(AbortHandler);
// check number of command line parameters
if (args.Length < 1)
Usage("Not enough arguments.");
// read command line parameters
string method = args[0];
RecommenderParameters parameters = null;
try { parameters = new RecommenderParameters(args, 1); }
catch (ArgumentException e) { Usage(e.Message); }
// arguments for iteration search
find_iter = parameters.GetRemoveInt32( "find_iter", 0);
max_iter = parameters.GetRemoveInt32( "max_iter", 500);
epsilon = parameters.GetRemoveDouble( "epsilon", 1);
err_cutoff = parameters.GetRemoveDouble( "err_cutoff", 2);
// data arguments
string data_dir = parameters.GetRemoveString( "data_dir");
if (data_dir != string.Empty)
data_dir = data_dir + "/mml-track2";
else
data_dir = "mml-track2";
sample_data = parameters.GetRemoveBool( "sample_data", false);
predict_rated = parameters.GetRemoveBool( "predict_rated", false);
predict_score = parameters.GetRemoveBool( "predict_score", false);
// other arguments
save_model_file = parameters.GetRemoveString( "save_model");
load_model_file = parameters.GetRemoveString( "load_model");
int random_seed = parameters.GetRemoveInt32( "random_seed", -1);
prediction_file = parameters.GetRemoveString( "prediction_file");
if (predict_rated)
predict_score = true;
Console.Error.WriteLine("predict_score={0}", predict_score);
if (random_seed != -1)
MyMediaLite.Util.Random.InitInstance(random_seed);
recommender_validate = Recommender.CreateItemRecommender(method);
if (recommender_validate == null)
Usage(string.Format("Unknown method: '{0}'", method));
Recommender.Configure(recommender_validate, parameters, Usage);
recommender_final = recommender_validate.Clone() as ItemRecommender;
if (parameters.CheckForLeftovers())
Usage(-1);
// load all the data
LoadData(data_dir);
if (load_model_file != string.Empty)
{
Recommender.LoadModel(recommender_validate, load_model_file + "-validate");
Recommender.LoadModel(recommender_final, load_model_file + "-final");
}
Console.Write(recommender_validate.ToString());
DoTrack2();
}
