static void LoadData()
{
TimeSpan loading_time = Utils.MeasureTime(delegate() {
// training data
training_data = ItemRecommendation.Read(Path.Combine(data_dir, training_file), user_mapping, item_mapping);
// relevant users and items
if (relevant_users_file != null)
{
relevant_users = new HashSet <int>(user_mapping.ToInternalID(Utils.ReadIntegers(Path.Combine(data_dir, relevant_users_file))));
}
else
{
relevant_users = training_data.AllUsers;
}
if (relevant_items_file != null)
{
relevant_items = new HashSet <int>(item_mapping.ToInternalID(Utils.ReadIntegers(Path.Combine(data_dir, relevant_items_file))));
}
else
{
relevant_items = training_data.AllItems;
}
if (!(recommender is MyMediaLite.ItemRecommendation.Random))
{
((ItemRecommender)recommender).Feedback = training_data;
}
// user attributes
if (recommender is IUserAttributeAwareRecommender)
{
if (user_attributes_file == null)
{
Usage("Recommender expects --user-attributes=FILE.");
}
else
{
((IUserAttributeAwareRecommender)recommender).UserAttributes = AttributeData.Read(Path.Combine(data_dir, user_attributes_file), user_mapping);
}
}
// item attributes
if (recommender is IItemAttributeAwareRecommender)
{
if (item_attributes_file == null)
{
Usage("Recommender expects --item-attributes=FILE.");
}
else
{
((IItemAttributeAwareRecommender)recommender).ItemAttributes = AttributeData.Read(Path.Combine(data_dir, item_attributes_file), item_mapping);
}
}
if (filtered_eval)
{
if (item_attributes_file == null)
{
Usage("--filtered-evaluation expects --item-attributes=FILE.");
}
else
{
item_attributes = AttributeData.Read(Path.Combine(data_dir, item_attributes_file), item_mapping);
}
}
// user relation
if (recommender is IUserRelationAwareRecommender)
{
if (user_relations_file == null)
{
Usage("Recommender expects --user-relation=FILE.");
}
else
{
((IUserRelationAwareRecommender)recommender).UserRelation = RelationData.Read(Path.Combine(data_dir, user_relations_file), user_mapping);
Console.WriteLine("relation over {0} users", ((IUserRelationAwareRecommender)recommender).NumUsers); // TODO move to DisplayDataStats
}
}
// item relation
if (recommender is IItemRelationAwareRecommender)
{
if (user_relations_file == null)
{
Usage("Recommender expects --item-relation=FILE.");
}
else
{
((IItemRelationAwareRecommender)recommender).ItemRelation = RelationData.Read(Path.Combine(data_dir, item_relations_file), item_mapping);
Console.WriteLine("relation over {0} items", ((IItemRelationAwareRecommender)recommender).NumItems); // TODO move to DisplayDataStats
}
}
// test data
if (test_ratio == 0)
{
if (test_file != null)
{
test_data = ItemRecommendation.Read(Path.Combine(data_dir, test_file), user_mapping, item_mapping);
}
}
else
{
var split = new PosOnlyFeedbackSimpleSplit <PosOnlyFeedback <SparseBooleanMatrix> >(training_data, test_ratio);
training_data = split.Train[0];
test_data = split.Test[0];
}
});
Console.Error.WriteLine(string.Format(CultureInfo.InvariantCulture, "loading_time {0,0:0.##}", loading_time.TotalSeconds));
}
static void LoadData()
{
TimeSpan loading_time = Utils.MeasureTime(delegate() {
// training data
training_data = ItemRecommendation.Read(Path.Combine(data_dir, training_file), user_mapping, item_mapping);
// relevant users and items
if (relevant_users_file != null)
relevant_users = new HashSet<int>(user_mapping.ToInternalID(Utils.ReadIntegers(Path.Combine(data_dir, relevant_users_file))));
else
relevant_users = training_data.AllUsers;
if (relevant_items_file != null)
relevant_items = new HashSet<int>(item_mapping.ToInternalID(Utils.ReadIntegers(Path.Combine(data_dir, relevant_items_file))));
else
relevant_items = training_data.AllItems;
if (! (recommender is MyMediaLite.ItemRecommendation.Random))
((ItemRecommender)recommender).Feedback = training_data;
// user attributes
if (recommender is IUserAttributeAwareRecommender)
{
if (user_attributes_file == null)
Usage("Recommender expects --user-attributes=FILE.");
else
((IUserAttributeAwareRecommender)recommender).UserAttributes = AttributeData.Read(Path.Combine(data_dir, user_attributes_file), user_mapping);
}
// item attributes
if (recommender is IItemAttributeAwareRecommender)
{
if (item_attributes_file == null)
Usage("Recommender expects --item-attributes=FILE.");
else
((IItemAttributeAwareRecommender)recommender).ItemAttributes = AttributeData.Read(Path.Combine(data_dir, item_attributes_file), item_mapping);
}
if (filtered_eval)
{
if (item_attributes_file == null)
Usage("--filtered-evaluation expects --item-attributes=FILE.");
else
item_attributes = AttributeData.Read(Path.Combine(data_dir, item_attributes_file), item_mapping);
}
// user relation
if (recommender is IUserRelationAwareRecommender)
if (user_relations_file == null)
{
Usage("Recommender expects --user-relation=FILE.");
}
else
{
((IUserRelationAwareRecommender)recommender).UserRelation = RelationData.Read(Path.Combine(data_dir, user_relations_file), user_mapping);
Console.WriteLine("relation over {0} users", ((IUserRelationAwareRecommender)recommender).NumUsers); // TODO move to DisplayDataStats
}
// item relation
if (recommender is IItemRelationAwareRecommender)
if (user_relations_file == null)
{
Usage("Recommender expects --item-relation=FILE.");
}
else
{
((IItemRelationAwareRecommender)recommender).ItemRelation = RelationData.Read(Path.Combine(data_dir, item_relations_file), item_mapping);
Console.WriteLine("relation over {0} items", ((IItemRelationAwareRecommender)recommender).NumItems); // TODO move to DisplayDataStats
}
// test data
if (test_ratio == 0)
{
if (test_file != null)
test_data = ItemRecommendation.Read(Path.Combine(data_dir, test_file), user_mapping, item_mapping);
}
else
{
var split = new PosOnlyFeedbackSimpleSplit<PosOnlyFeedback<SparseBooleanMatrix>>(training_data, test_ratio);
training_data = split.Train[0];
test_data = split.Test[0];
}
});
Console.Error.WriteLine(string.Format(CultureInfo.InvariantCulture, "loading_time {0,0:0.##}", loading_time.TotalSeconds));
}
protected override void LoadData()
{
TimeSpan loading_time = Wrap.MeasureTime(delegate() {
base.LoadData();
// training data
training_data = double.IsNaN(rating_threshold)
? ItemData.Read(training_file, user_mapping, item_mapping, file_format == ItemDataFileFormat.IGNORE_FIRST_LINE)
: ItemDataRatingThreshold.Read(training_file, rating_threshold, user_mapping, item_mapping, file_format == ItemDataFileFormat.IGNORE_FIRST_LINE);
// test data
if (test_ratio == 0)
{
if (test_file != null)
{
test_data = double.IsNaN(rating_threshold)
? ItemData.Read(test_file, user_mapping, item_mapping, file_format == ItemDataFileFormat.IGNORE_FIRST_LINE)
: ItemDataRatingThreshold.Read(test_file, rating_threshold, user_mapping, item_mapping, file_format == ItemDataFileFormat.IGNORE_FIRST_LINE);
}
}
else
{
var split = new PosOnlyFeedbackSimpleSplit <PosOnlyFeedback <SparseBooleanMatrix> >(training_data, test_ratio);
training_data = split.Train[0];
test_data = split.Test[0];
}
if (user_prediction)
{
// swap file names for test users and candidate items
var ruf = test_users_file;
var rif = candidate_items_file;
test_users_file = rif;
candidate_items_file = ruf;
// swap user and item mappings
var um = user_mapping;
var im = item_mapping;
user_mapping = im;
item_mapping = um;
// transpose training and test data
training_data = training_data.Transpose();
// transpose test data
if (test_data != null)
{
test_data = test_data.Transpose();
}
}
for (int i = 0; i < recommenders.Count; i++)
{
if (recommenders[i] is MyMediaLite.ItemRecommendation.ItemRecommender)
{
((ItemRecommender)recommenders[i]).Feedback = training_data;
}
}
// test users
if (test_users_file != null)
{
test_users = user_mapping.ToInternalID(File.ReadLines(Path.Combine(data_dir, test_users_file)).ToArray());
}
else
{
test_users = test_data != null ? test_data.AllUsers : training_data.AllUsers;
}
// if necessary, perform user sampling
if (num_test_users > 0 && num_test_users < test_users.Count)
{
var old_test_users = new HashSet <int>(test_users);
var new_test_users = new int[num_test_users];
for (int i = 0; i < num_test_users; i++)
{
int random_index = MyMediaLite.Random.GetInstance().Next(old_test_users.Count - 1);
new_test_users[i] = old_test_users.ElementAt(random_index);
old_test_users.Remove(new_test_users[i]);
}
test_users = new_test_users;
}
// candidate items
if (candidate_items_file != null)
{
candidate_items = item_mapping.ToInternalID(File.ReadLines(Path.Combine(data_dir, candidate_items_file)).ToArray());
}
else if (all_items)
{
candidate_items = Enumerable.Range(0, item_mapping.InternalIDs.Max() + 1).ToArray();
}
if (candidate_items != null)
{
eval_item_mode = CandidateItems.EXPLICIT;
}
else if (in_training_items)
{
eval_item_mode = CandidateItems.TRAINING;
}
else if (in_test_items)
{
eval_item_mode = CandidateItems.TEST;
}
else if (overlap_items)
{
eval_item_mode = CandidateItems.OVERLAP;
}
else
{
eval_item_mode = CandidateItems.UNION;
}
});
//Salvar arquivos
List <string> linesToWrite = new List <string>();
for (int i = 0; i < training_data.UserMatrix.NumberOfRows; i++)
{
IList <int> columns = training_data.UserMatrix.GetEntriesByRow(i);
for (int j = 0; j < columns.Count; j++)
{
StringBuilder line = new StringBuilder();
line.Append(i.ToString() + " " + columns[j].ToString());
linesToWrite.Add(line.ToString());
}
}
System.IO.File.WriteAllLines("training.data", linesToWrite.ToArray());
linesToWrite = new List <string>();
for (int i = 0; i < test_data.UserMatrix.NumberOfRows; i++)
{
IList <int> columns = test_data.UserMatrix.GetEntriesByRow(i);
for (int j = 0; j < columns.Count; j++)
{
StringBuilder line = new StringBuilder();
line.Append(i.ToString() + " " + columns[j].ToString());
linesToWrite.Add(line.ToString());
}
}
System.IO.File.WriteAllLines("test.data", linesToWrite.ToArray());
/*
* List<string> linesToWrite = new List<string>();
* for (int rowIndex = 0; rowIndex < training_data.AllItems.Count; rowIndex++)
* {
*
* }*/
Console.Error.WriteLine(string.Format(CultureInfo.InvariantCulture, "loading_time {0,0:0.##}", loading_time.TotalSeconds));
Console.Error.WriteLine("memory {0}", Memory.Usage);
}
static void LoadData()
{
TimeSpan loading_time = Wrap.MeasureTime(delegate() {
// training data
training_file = Path.Combine(data_dir, training_file);
training_data = double.IsNaN(rating_threshold)
? ItemData.Read(training_file, user_mapping, item_mapping, file_format == ItemDataFileFormat.IGNORE_FIRST_LINE)
: ItemDataRatingThreshold.Read(training_file, rating_threshold, user_mapping, item_mapping, file_format == ItemDataFileFormat.IGNORE_FIRST_LINE);
// user attributes
if (user_attributes_file != null)
user_attributes = AttributeData.Read(Path.Combine(data_dir, user_attributes_file), user_mapping);
if (recommender is IUserAttributeAwareRecommender)
((IUserAttributeAwareRecommender)recommender).UserAttributes = user_attributes;
// item attributes
if (item_attributes_file != null)
item_attributes = AttributeData.Read(Path.Combine(data_dir, item_attributes_file), item_mapping);
if (recommender is IItemAttributeAwareRecommender)
((IItemAttributeAwareRecommender)recommender).ItemAttributes = item_attributes;
// user relation
if (recommender is IUserRelationAwareRecommender)
{
((IUserRelationAwareRecommender)recommender).UserRelation = RelationData.Read(Path.Combine(data_dir, user_relations_file), user_mapping);
Console.WriteLine("relation over {0} users", ((IUserRelationAwareRecommender)recommender).NumUsers);
}
// item relation
if (recommender is IItemRelationAwareRecommender)
{
((IItemRelationAwareRecommender)recommender).ItemRelation = RelationData.Read(Path.Combine(data_dir, item_relations_file), item_mapping);
Console.WriteLine("relation over {0} items", ((IItemRelationAwareRecommender)recommender).NumItems);
}
// user groups
if (user_groups_file != null)
{
group_to_user = RelationData.Read(Path.Combine(data_dir, user_groups_file), user_mapping); // assumption: user and user group IDs are disjoint
user_groups = group_to_user.NonEmptyRowIDs;
Console.WriteLine("{0} user groups", user_groups.Count);
}
// test data
if (test_ratio == 0)
{
if (test_file != null)
{
test_file = Path.Combine(data_dir, test_file);
test_data = double.IsNaN(rating_threshold)
? ItemData.Read(test_file, user_mapping, item_mapping, file_format == ItemDataFileFormat.IGNORE_FIRST_LINE)
: ItemDataRatingThreshold.Read(test_file, rating_threshold, user_mapping, item_mapping, file_format == ItemDataFileFormat.IGNORE_FIRST_LINE);
}
}
else
{
var split = new PosOnlyFeedbackSimpleSplit<PosOnlyFeedback<SparseBooleanMatrix>>(training_data, test_ratio);
training_data = split.Train[0];
test_data = split.Test[0];
}
if (group_method == "GroupsAsUsers")
{
Console.WriteLine("group recommendation strategy: {0}", group_method);
// TODO verify what is going on here
//var training_data_group = new PosOnlyFeedback<SparseBooleanMatrix>();
// transform groups to users
foreach (int group_id in group_to_user.NonEmptyRowIDs)
foreach (int user_id in group_to_user[group_id])
foreach (int item_id in training_data.UserMatrix.GetEntriesByRow(user_id))
training_data.Add(group_id, item_id);
// add the users that do not belong to groups
//training_data = training_data_group;
// transform groups to users
var test_data_group = new PosOnlyFeedback<SparseBooleanMatrix>();
foreach (int group_id in group_to_user.NonEmptyRowIDs)
foreach (int user_id in group_to_user[group_id])
foreach (int item_id in test_data.UserMatrix.GetEntriesByRow(user_id))
test_data_group.Add(group_id, item_id);
test_data = test_data_group;
group_method = null; // deactivate s.t. the normal eval routines are used
}
if (user_prediction)
{
// swap file names for test users and candidate items
var ruf = test_users_file;
var rif = candidate_items_file;
test_users_file = rif;
candidate_items_file = ruf;
// swap user and item mappings
var um = user_mapping;
var im = item_mapping;
user_mapping = im;
item_mapping = um;
// transpose training and test data
training_data = training_data.Transpose();
// transpose test data
if (test_data != null)
test_data = test_data.Transpose();
}
if (recommender is MyMediaLite.ItemRecommendation.ItemRecommender)
((ItemRecommender)recommender).Feedback = training_data;
// test users
if (test_users_file != null)
test_users = user_mapping.ToInternalID( File.ReadLines(Path.Combine(data_dir, test_users_file)).ToArray() );
else
test_users = test_data != null ? test_data.AllUsers : training_data.AllUsers;
// if necessary, perform user sampling
if (num_test_users > 0 && num_test_users < test_users.Count)
{
var old_test_users = new HashSet<int>(test_users);
var new_test_users = new int[num_test_users];
for (int i = 0; i < num_test_users; i++)
{
int random_index = MyMediaLite.Util.Random.GetInstance().Next(old_test_users.Count - 1);
new_test_users[i] = old_test_users.ElementAt(random_index);
old_test_users.Remove(new_test_users[i]);
}
test_users = new_test_users;
}
// candidate items
if (candidate_items_file != null)
candidate_items = item_mapping.ToInternalID( File.ReadLines(Path.Combine(data_dir, candidate_items_file)).ToArray() );
else if (all_items)
candidate_items = Enumerable.Range(0, item_mapping.InternalIDs.Max() + 1).ToArray();
if (candidate_items != null)
eval_item_mode = CandidateItems.EXPLICIT;
else if (in_training_items)
eval_item_mode = CandidateItems.TRAINING;
else if (in_test_items)
eval_item_mode = CandidateItems.TEST;
else if (overlap_items)
eval_item_mode = CandidateItems.OVERLAP;
else
eval_item_mode = CandidateItems.UNION;
});
Console.Error.WriteLine(string.Format(CultureInfo.InvariantCulture, "loading_time {0,0:0.##}", loading_time.TotalSeconds));
Console.Error.WriteLine("memory {0}", Memory.Usage);
}
