public void menu()
{
TratamentoArquivo c2 = new TratamentoArquivo();
int op;
do
{
Console.WriteLine("1 - Abrir Datasset");
Console.WriteLine("2 - Concatenar");
Console.WriteLine("3 - Gerar Kfolds");
Console.WriteLine("4 - Gerar Training Test");
Console.WriteLine("0 - Sair");
op = Int32.Parse(Console.ReadLine());
switch (op)
{
case 1:
Console.Clear();
c2.Abrir(); break;
case 2:
Console.Clear();
c2.Concatenar(); break;
case 3:
Console.Clear();
Console.WriteLine("Entre com a quantidade de k folds desejada");
qtdKfolds = Int32.Parse(Console.ReadLine());
c2.Alterar(qtdKfolds); break;
case 4:
Console.Clear();
Console.WriteLine("Entre com a porcentagem do test desejada");
percentTest = Int32.Parse(Console.ReadLine());
c2.gerarTestTrainingSet(qtdKfolds, percentTest); break;
}
} while (op != 0);
}
protected void Run(string[] args)
{
Console.WriteLine("WISER-RecSys começou");
options = new OptionSet()
{
// string-valued options
{ "arquivo=", v => arquivo = v },
{ "measures=", v => measures = v },
{ "recommender-options=", v => recommender_options += " " + v },
{ "help", v => show_help = v != null },
};
eval_measures = ItemRecommendationEvaluationResults.DefaultMeasuresToShow;
IList <string> extra_args = options.Parse(args);
if (show_help)
{
Usage(0);
}
//eval
if (measures != null)
{
eval_measures = measures.Split(' ', ',');
}
TratamentoArquivo tratamentoarquivo = new TratamentoArquivo();
tratamentoarquivo.menu();
for (contador = 1; contador < 10; contador++)
{
//Rodar o de vocs
// tratamentoarquivo.Alterar(quantidadekfold);
//
training_file = @"C:\Users\" + Environment.UserName + @"\Desktop\RecSys\RecSys\RecSys\bin\Debug\Kfold-pasta-" + contador + @"\training.data";
test_file = @"C:\Users\" + Environment.UserName + @"\Desktop\RecSys\RecSys\RecSys\bin\Debug\Kfold-pasta-" + contador + @"\test.data";
training_partial_file = "training.partial.data";
test_partial_file = "test.partial.data";
for (int i = 0; i < arquivos.Length; i++)
{
MyMediaLite.Random.Seed = 1;
item_attributes_file = "movie_" + arquivos[i] + ".dat_saida";
user_mapping.Add(new Mapping());
item_mapping.Add(new Mapping());
//Setup recommender
recommenders.Add("BPRMFAttr".CreateItemRecommender());
recommenders[i].Configure(recommender_options, (string msg) =>
{
Console.Error.WriteLine(msg); Environment.Exit(-1);
});
// item attributes
if (recommenders[i] is IItemAttributeAwareRecommender && item_attributes_file == null)
{
Abort("Recommender expects --item-attributes=FILE.");
}
if (item_attributes_file != null)
{
item_attributes.Add(AttributeData.Read(item_attributes_file, item_mapping[i]));
}
if (recommenders[i] is IItemAttributeAwareRecommender)
{
((IItemAttributeAwareRecommender)recommenders[i]).ItemAttributes = item_attributes[i];
}
IBooleanMatrix lista_vazia = new SparseBooleanMatrix();
if (recommenders[i] is IUserAttributeAwareRecommender)
{
((IUserAttributeAwareRecommender)recommenders[i]).UserAttributes = lista_vazia;
}
// training data
training_data.Add(ItemData.Read(training_file, user_mapping[i], item_mapping[i], false));
test_data.Add(ItemData.Read(test_file, user_mapping[i], item_mapping[i], false));
test_users.Add(test_data[i].AllUsers);
//Probe
training_probe_data.Add(ItemData.Read(training_partial_file, user_mapping[i], item_mapping[i], false));
test_probe_data.Add(ItemData.Read(test_partial_file, user_mapping[i], item_mapping[i], false));
if (recommenders[i] is MyMediaLite.ItemRecommendation.ItemRecommender)
{
((ItemRecommender)recommenders[i]).Feedback = training_probe_data[i];
}
//Trainar
Console.WriteLine("Vamos ao probe training");
var train_time_span = Wrap.MeasureTime(delegate() { recommenders[i].Train(); });
Console.WriteLine("training_time " + train_time_span + " ");
}
Evaluation evaluation = new Evaluation(recommenders, test_probe_data, training_probe_data);
//Probe learn
Console.WriteLine("Probe learn started");
TimeSpan time_span = Wrap.MeasureTime(delegate() { evaluation.EvaluateProbe(test_users, user_mapping, item_mapping); });
Console.WriteLine(" Probe learn time: " + time_span);
for (int i = 0; i < arquivos.Length; i++)
{
MyMediaLite.Random.Seed = 1;
item_attributes_file = "movie_" + arquivos[i] + ".dat_saida";
//Setup recommender
recommenders[i] = "BPRMFAttr".CreateItemRecommender();
recommenders[i].Configure(recommender_options, (string msg) => { Console.Error.WriteLine(msg); Environment.Exit(-1); });
// item attributes
if (recommenders[i] is IItemAttributeAwareRecommender && item_attributes_file == null)
{
Abort("Recommender expects --item-attributes=FILE.");
}
if (recommenders[i] is IItemAttributeAwareRecommender)
{
((IItemAttributeAwareRecommender)recommenders[i]).ItemAttributes = item_attributes[i];
}
IBooleanMatrix lista_vazia = new SparseBooleanMatrix();
if (recommenders[i] is IUserAttributeAwareRecommender)
{
((IUserAttributeAwareRecommender)recommenders[i]).UserAttributes = lista_vazia;
}
if (recommenders[i] is MyMediaLite.ItemRecommendation.ItemRecommender)
{
((ItemRecommender)recommenders[i]).Feedback = training_data[i];
}
//Trainar
Console.WriteLine("Agora ao treino normal");
var train_time_span = Wrap.MeasureTime(delegate() { recommenders[i].Train(); });
Console.WriteLine("training_time " + train_time_span + " ");
}
var results = evaluation.Evaluate(test_data, training_data, test_users, user_mapping, item_mapping);
foreach (EvaluationResults result in results)
{
Console.WriteLine(result.ToString());
}
Console.WriteLine("Press any key to continue...");
Console.ReadKey();
}
}
