//*********** GlobalAverage Recommender
public List <int> getBestItemsGlobalAverage(string dataset, int userid, int recs)
{
var mydata = RatingData.Read(dataset);
//Create the recommender
var recommenderGlobalAverage = new MyMediaLite.RatingPrediction.GlobalAverage();
//Give it the dataset
recommenderGlobalAverage.Ratings = mydata;
//Train it
recommenderGlobalAverage.Train();
/////////////
// Make the predictions
var user_recs = recommenderGlobalAverage.Recommend(userid, recs);
// get the recommendations
foreach (var i in user_recs)
{
mylist.Add(i.Item1);
}
return(mylist);
}
protected override void LoadData()
{
bool static_data = !online_eval;
TimeSpan loading_time = Wrap.MeasureTime(delegate() {
base.LoadData();
// read training data
if ((recommender is TimeAwareRatingPredictor || chronological_split != null) && file_format != RatingFileFormat.MOVIELENS_1M)
{
training_data = TimedRatingData.Read(training_file, user_mapping, item_mapping);
}
else
{
if (file_format == RatingFileFormat.DEFAULT)
{
training_data = static_data
? StaticRatingData.Read(training_file, user_mapping, item_mapping, rating_type)
: RatingData.Read(training_file, user_mapping, item_mapping);
}
else if (file_format == RatingFileFormat.IGNORE_FIRST_LINE)
{
training_data = static_data
? StaticRatingData.Read(training_file, user_mapping, item_mapping, rating_type, TestRatingFileFormat.WITH_RATINGS, true)
: RatingData.Read(training_file, user_mapping, item_mapping, true);
}
else if (file_format == RatingFileFormat.MOVIELENS_1M)
{
training_data = MovieLensRatingData.Read(training_file, user_mapping, item_mapping);
}
else if (file_format == RatingFileFormat.KDDCUP_2011)
{
training_data = MyMediaLite.IO.KDDCup2011.Ratings.Read(training_file);
}
}
recommender.Ratings = training_data;
// read test data
if (test_file != null)
{
TestRatingFileFormat test_format = test_no_ratings ? TestRatingFileFormat.WITHOUT_RATINGS : TestRatingFileFormat.WITH_RATINGS;
if (recommender is TimeAwareRatingPredictor && file_format != RatingFileFormat.MOVIELENS_1M)
{
test_data = TimedRatingData.Read(test_file, user_mapping, item_mapping, test_format);
}
else if (file_format == RatingFileFormat.MOVIELENS_1M)
{
test_data = MovieLensRatingData.Read(test_file, user_mapping, item_mapping, test_format);
}
else if (file_format == RatingFileFormat.KDDCUP_2011)
{
test_data = MyMediaLite.IO.KDDCup2011.Ratings.Read(test_file);
}
else
{
test_data = StaticRatingData.Read(test_file, user_mapping, item_mapping, rating_type, test_format, file_format == RatingFileFormat.IGNORE_FIRST_LINE);
}
if (recommender is ITransductiveRatingPredictor)
{
((ITransductiveRatingPredictor)recommender).AdditionalFeedback = test_data;
}
}
});
Console.Error.WriteLine(string.Format(CultureInfo.InvariantCulture, "loading_time {0:0.##}", loading_time.TotalSeconds));
Console.Error.WriteLine("memory {0}", Memory.Usage);
}
protected BaseRatingAdjustment(IParsedReview review)
{
Review = review ?? throw new System.ArgumentNullException(nameof(review));
calculatedSentiments = new Dictionary <IWordItem, SentimentValue>(SimpleWordItemEquality.Instance);
Rating = new RatingData();
}
// default constructor
public EvaluationModels(string dataset)
{
mydata = RatingData.Read(dataset);
}
static void Main(string[] args)
{
String path_training_data = "user_ratedmovies.dat";
String path_user_data = "users.dat";
String path_atr_data = "movie_genres.dat";
String path_pred_data = "predict.dat";
var user_mapping = new Mapping();
var item_mapping = new Mapping();
//var user_mapping = new EntityMapping();
//var item_mapping = new EntityMapping();
//String path_training_data = "1.rec.train";
//String path_test_data = "1.rec.test";
//String path_training_data = "u1.base";
//String path_test_data = "u1.test";
//var training_data = ItemData.Read(path_training_data);
//var test_data = ItemData.Read(path_test_data);
var training_data = RatingData.Read(path_training_data, user_mapping, item_mapping);
var relevant_items = item_mapping.InternalIDs;
var atr_data = AttributeData.Read(path_atr_data, item_mapping);
var pred_data = RatingData.Read(path_pred_data, user_mapping, item_mapping);
//var user_data = ItemData.Read(path_user_data, user_mapping);
Console.WriteLine("I'm here");
//Console.WriteLine(String.Join(";", user_data.AllUsers));
//var test_data = RatingData.Read(path_test_data);
//var recommender = new ItemKNN();
//recommender.Feedback = training_data;
//recommender.Train();
//var recommender = new GSVDPlusPlus();
//var recommender = new MatrixFactorization();
//recommender.Ratings = training_data;
// recommender.MaxRating = 5;
// recommender.MinRating = 1;
//recommender.ItemAttributes = atr_data;
//recommender.NumFactors = 5;
//recommender.NumIter = 10;
//recommender.Train();
var recommender = new SVDPlusPlus();
recommender.Ratings = training_data;
//recommender.AdditionalFeedback = user_data;
Console.WriteLine("I'm here2");
Console.WriteLine(recommender.ToString());
//recommender.ItemAttributes = atr_data;
recommender.NumFactors = 10;
Console.WriteLine("I'm here3");
Console.WriteLine(recommender.ToString());
recommender.Train();
Console.WriteLine("I'm here4");
//var results = recommender.DoIterativeCrossValidation(recommdender, 10, 1, 1, true);
var results = recommender.DoCrossValidation(10, false, true);
////var results = recommender.Evaluate(test_data, training_data);
foreach (var key in results.Keys)
{
Console.WriteLine("{0}={1}", key, results[key]);
}
Console.WriteLine(results);
//recommender.Predict();
recommender.WritePredictions(pred_data, "test45.dat", user_mapping, item_mapping, "{0}|{1}|{2}");
Console.WriteLine(recommender.Predict(1, 1));
Console.ReadLine();
}
private string Processing(NameValueCollection par)
{
string ret = string.Empty;
string[] allKeys = par.AllKeys;
if (allKeys.Contains("addr") &&
allKeys.Contains("userid") &&
allKeys.Contains("callback") &&
allKeys.Contains("cssreg"))
{
ret = Global.widgetNotFoundData;
string addr = HttpUtility.UrlDecode(par["addr"]).Trim();
string cssreg = HttpUtility.UrlDecode(par["cssreg"]).Trim();
if (!string.IsNullOrWhiteSpace(addr) && (1 < addr.Split(' ').Count()))
{
GeoMatching gm = new GeoMatching();
if (!addr.StartsWith("омск", StringComparison.InvariantCultureIgnoreCase))
{
addr = addr.Insert(0, "Омск ");
}
Coordinates cc = gm.GetCoordinates(addr);
if (null != cc)
{
NumberFormatInfo provider = new NumberFormatInfo();
provider.NumberDecimalSeparator = ".";
GeoCoordinate source = new GeoCoordinate(Convert.ToDouble(cc.Lng, provider), Convert.ToDouble(cc.Lat, provider));
Dictionary <int, Tuple <double, Guid> > schoolDistance = new Dictionary <int, Tuple <double, Guid> >();
foreach (KeyValuePair <Guid, SchoolData> item in Global.schoolDict)
{
double dist = item.Value.pointOnMap.GetDistanceTo(source);
Tuple <double, Guid> dataExist;
if (schoolDistance.TryGetValue(item.Value.school, out dataExist))
{
if (dist < dataExist.Item1)
{
schoolDistance[item.Value.school] = Tuple.Create <double, Guid>(dist, item.Key);
}
}
else
{
schoolDistance.Add(item.Value.school, Tuple.Create <double, Guid>(dist, item.Key));
}
}
schoolDistance = schoolDistance.OrderBy(x => x.Value.Item1).Take(5).ToDictionary(x => x.Key, x => x.Value);
string tableBody = string.Empty;
foreach (KeyValuePair <int, Tuple <double, Guid> > item in schoolDistance)
{
SchoolData sd = Global.schoolDict[item.Value.Item2];
RatingData rd = null;
Global.ratingDict.TryGetValue(item.Key, out rd);
GenerateWidgetRow(ref tableBody, Global.patternWidjetRow, sd, item.Value.Item1, rd);
}
if ("0" == cssreg)
{
ret = string.Empty;
}
else
{
ret = Global.patternWidjetStyle;
}
ret += Global.patternWidjetBody.Replace(Global.rowStart, string.Empty)
.Replace(Global.rowEnd, string.Empty)
.Replace(Global.patternWidjetRow, tableBody);
}
}
ret = ret.Replace(Environment.NewLine, string.Empty);
string callBackName = par["callback"];
ret = string.Concat(callBackName, ".Callback('", ret, "');");
}
return(ret);
}
private void GenerateWidgetRow(ref string ret, string pattern, SchoolData sd, double?distance, RatingData rd)
{
string row = pattern;
row = row.Replace("{school_num}", sd.school.ToString());
string adr = string.Concat("ул. ", sd.street, " д.", sd.buildNum);
row = row.Replace("{address}", adr);
string distStr = string.Empty;
if ((distance.HasValue) && (40 < distance.Value))
{
distStr = string.Concat("Расстояние:<br/>", DistanceFormat.InKiloMeters(distance.Value));
}
row = row.Replace("{distance}", distStr);
if (null != rd)
{
row = row.Replace("{common_raiting}", rd.egCommonRating);
row = row.Replace("{common_level}", rd.egCommomLevel);
row = row.Replace("{common_raiting_level}", rd.egCommonState);
string ratingStyle = string.Empty;
switch (rd.egCommonState)
{
case "Средний": { ratingStyle = "schoollist_item_data_middle_level"; break; }
case "Ниже среднего": { ratingStyle = "schoollist_item_data_low_middle_level"; break; }
case "Выше среднего": { ratingStyle = "schoollist_item_data_high_middle_level"; break; }
case "Самый высокий": { ratingStyle = "schoollist_item_data_high_level"; break; }
case "Самый низкий": { ratingStyle = "schoollist_item_data_low_level"; break; }
}
row = row.Replace("{common_raiting_level_style}", ratingStyle);
Global.EnableBlock(ref row, "RAITING DATA");
Global.DisableBlock(ref row, "NORAITING DATA");
}
else
{
Global.EnableBlock(ref row, "NORAITING DATA");
Global.DisableBlock(ref row, "RAITING DATA");
}
ret = ret + row;
}
private void GenerateWidgetData(ref string wigetPattern, int schoolNum, IEnumerable <SchoolData> schoolList, RatingData rd)
{
wigetPattern = wigetPattern.Replace("{school_num}", schoolNum.ToString());
string addrList = string.Empty;
foreach (SchoolData sd in schoolList)
{
addrList += string.Concat("ул. ", sd.street, " д.", sd.buildNum, "<br/>");
}
if (string.IsNullOrWhiteSpace(addrList))
{
addrList = "Нет данных";
}
wigetPattern = wigetPattern.Replace("{address}", addrList);
if (null != rd)
{
wigetPattern = wigetPattern.Replace("{common_raiting}", rd.egCommonRating);
wigetPattern = wigetPattern.Replace("{common_level}", rd.egCommomLevel);
wigetPattern = wigetPattern.Replace("{common_raiting_level}", rd.egCommonState);
string ratingStyle = string.Empty;
switch (rd.egCommonState)
{
case "Средний": { ratingStyle = "schooldata_item_data_middle_level"; break; }
case "Ниже среднего": { ratingStyle = "schooldata_item_data_low_middle_level"; break; }
case "Выше среднего": { ratingStyle = "schooldata_item_data_high_middle_level"; break; }
case "Самый высокий": { ratingStyle = "schooldata_item_data_high_level"; break; }
case "Самый низкий": { ratingStyle = "schooldata_item_data_low_level"; break; }
}
wigetPattern = wigetPattern.Replace("{common_raiting_level_style}", ratingStyle);
Global.EnableBlock(ref wigetPattern, "RAITING DATA");
Global.DisableBlock(ref wigetPattern, "NORAITING DATA");
}
else
{
Global.EnableBlock(ref wigetPattern, "NORAITING DATA");
Global.DisableBlock(ref wigetPattern, "RAITING DATA");
}
}
public ProductTypes.Rating Convert(RatingData r)
{
if (r == null) return new ProductTypes.Rating
(
0,
0
);
return new ProductTypes.Rating
(
r.score,
(int)r.count
);
}
public static void Main(string[] args)
{
// TODO add random seed
// TODO report per-user times
string data_file = args[0];
string method = args[1];
string options = args[2];
int num_test_users = int.Parse(args[3]);
// load the data
var all_data = RatingData.Read(data_file);
// TODO randomize
var test_users = new HashSet <int>(Enumerable.Range(0, num_test_users));
var update_indices = new List <int>();
var eval_indices = new List <int>();
foreach (int user_id in test_users)
{
if (all_data.ByUser[user_id].Count > 1)
{
var user_indices = all_data.ByUser[user_id];
for (int i = 0; i < user_indices.Count - 1; i++)
{
update_indices.Add(user_indices[i]);
}
for (int i = user_indices.Count - 1; i < user_indices.Count; i++)
{
eval_indices.Add(user_indices[i]);
}
}
}
var training_indices = new List <int>();
for (int i = 0; i < all_data.Count; i++)
{
if (!test_users.Contains(all_data.Users[i]))
{
training_indices.Add(i);
}
}
var training_data = new MyMediaLite.Data.Ratings();
foreach (int i in training_indices)
{
training_data.Add(all_data.Users[i], all_data.Items[i], all_data[i]);
}
var update_data = new RatingsProxy(all_data, update_indices);
var eval_data = new RatingsProxy(all_data, eval_indices);
Console.Write(training_data.Statistics());
Console.Write(update_data.Statistics());
Console.Write(eval_data.Statistics());
// prepare recommender
RatingPredictor recommender = method.CreateRatingPredictor();
recommender.Configure(options);
recommender.Ratings = training_data;
Console.WriteLine(string.Format(CultureInfo.InvariantCulture, "ratings range: [{0}, {1}]", recommender.MinRating, recommender.MaxRating));
Console.WriteLine("recommender: {0}", recommender);
recommender.Train();
// I. complete retraining
Console.WriteLine(
"complete training: {0}",
recommender.EvaluateFoldInCompleteRetraining(update_data, eval_data));
// II. online updates
Console.WriteLine(
"incremental training: {0}",
((IncrementalRatingPredictor)recommender).EvaluateFoldInIncrementalTraining(update_data, eval_data));
// III. fold-in
Console.WriteLine(
"fold-in: {0}",
((IFoldInRatingPredictor)recommender).EvaluateFoldIn(update_data, eval_data));
}
///
public override void Train()
{
external_scores = RatingData.Read(PredictionFile, UserMapping, ItemMapping);
}
protected void Application_Start(object sender, EventArgs e)
{
// Не стартуем пока ПОЛНОСТЬЮ не подготовим все данные !!!
// wfFacade = new Facade();
string line;
JavaScriptSerializer js = new JavaScriptSerializer();
StreamReader file = new StreamReader(Server.MapPath("~\\data\\SchoolData.txt"));
using (file)
{
while ((line = file.ReadLine()) != null)
{
SchoolData sc = js.Deserialize <SchoolData>(line);
sc.pointOnMap = new GeoCoordinate(sc.lattitude, sc.longtitude);
schoolDict.Add(Guid.NewGuid(), sc);
}
}
file = new StreamReader(Server.MapPath("~\\data\\RatingData.txt"));
using (file)
{
while ((line = file.ReadLine()) != null)
{
RatingData rd = js.Deserialize <RatingData>(line);
ratingDict.Add(rd.school, rd);
}
}
patternWidjetSchoolList = File.ReadAllText(Server.MapPath("~\\widjets\\schoollistrow.html"));
patternWidjetStyle = getWidgetStyle(patternWidjetSchoolList);
patternWidjetRow = getWidgetRow(patternWidjetSchoolList);
patternWidjetBody = getWidgetBody(patternWidjetSchoolList);
widgetNotFoundData = File.ReadAllText(Server.MapPath("~\\widjets\\NoFoundData.html"));
widgetNotFoundAddressStyle = getWidgetStyle(widgetNotFoundData);
widgetNotFoundAddressBody = getWidgetBody(widgetNotFoundData);
patternWidjetSchoolData = File.ReadAllText(Server.MapPath("~\\widjets\\schooldata.html"));
patternWidjetSchoolDataStyle = getWidgetStyle(patternWidjetSchoolData);
patternWidjetSchoolDataBody = getWidgetBody(patternWidjetSchoolData);
patternWidjetSchoolMap = File.ReadAllText(Server.MapPath("~\\widjets\\schoolmap.html"));
patternOlympicWidjet = File.ReadAllText(Server.MapPath("~\\widjets\\olympic.html"));
patternOlympicWidjetStyle = getWidgetStyle(patternOlympicWidjet);
patternOlympicWidjetBody = getWidgetBody(patternOlympicWidjet);
patternOlympicWidjetFarmes = File.ReadAllText(Server.MapPath("~\\widjets\\olympicFrames.html"));
patternWFWidjet = File.ReadAllText(Server.MapPath("~\\widjets\\WF.html"));
patternWFWidjetStyle = getWidgetStyle(patternWFWidjet);
patternWFWidjetBody = getWidgetBody(patternWFWidjet);
}
static void Main(string[] args)
{
string folder = args.Length != 1 ? @"..\..\Resources\" : args[0];
Console.WriteLine($"{GetTimeStamp()} Files must be in folder {folder}. Use the first argument to specify another folder.");
Console.Write($"{GetTimeStamp()} Enter # of neighbors [50-10000]: ");
int neighbors;
if (!int.TryParse(Console.ReadLine(), out neighbors))
{
Console.Write("Unable to parse input.");
}
else
{
neighbors = neighbors < 50 ? 50 : (neighbors > 10000 ? 10000 : neighbors);
}
Console.WriteLine($"{GetTimeStamp()} neighbors set to: {neighbors}");
Console.WriteLine($"{GetTimeStamp()} Loading data...");
const string moviesFile = "movie_titles.txt";
const string trainingRatingsFile = "TrainingRatings.txt";
const string testRatingsFile = "TestingRatings.txt";
// ReSharper disable once UnusedVariable
MovieData movies = ParseMoviesData(File.ReadAllLines(Path.Combine(folder, moviesFile)));
RatingData trainingRatings = ParseRatingData(File.ReadAllLines(Path.Combine(folder, trainingRatingsFile)));
RatingData testRatings = ParseRatingData(File.ReadAllLines(Path.Combine(folder, testRatingsFile)));
Console.WriteLine($"{GetTimeStamp()} Done.");
DateTime now = DateTime.Now;
long index = 0;
var results = new List <Tuple <double /*predicted*/, double /*actual*/> >();
//Parallel.ForEach(testRatings.GetUsers().TakeWhile(x => Interlocked.Read(ref index) < 5000), userId =>
Parallel.ForEach(testRatings.GetUsers(), userId =>
{
if (Interlocked.Add(ref index, 1) % 100 == 0)
{
PrintProgress(index, now, testRatings.GetUsersCount());
}
var ratings = testRatings.GetUserRatings(userId);
foreach (var movieRating in ratings)
{
double actual = movieRating.Value;
double predicted = trainingRatings.PredictMovieRating(userId, movieRating.Key, neighbors);
lock (results)
results.Add(new Tuple <double, double>(predicted, actual));
}
});
PrintProgress(index, now, testRatings.GetUsersCount());
double mae = CalculateMAE(results);
double mape = CalculateMAPE(results);
double rmsd = CalculateRMSD(results);
Console.WriteLine();
Console.WriteLine($"{GetTimeStamp()} MAE={mae} (Mean Absolute Error)");
Console.WriteLine($"{GetTimeStamp()} MAPE={mape} (Mean Absolute Percentage Error)");
Console.WriteLine($"{GetTimeStamp()} RMSD={rmsd} (Root-mean-square deviation)");
}
private async Task <List <string> > GetEventsRating(int superConferenceId)
{
var output = new List <RatingData>();
var superConference = await _context.SuperConferences
.Include(c => c.Conferences)
.FirstOrDefaultAsync(m => m.Id == superConferenceId);
var conferences = superConference.Conferences.ToList();
var eEvents = await _context.Events
.Where(e => e.Conference.SuperConferenceId == superConferenceId)
.ToListAsync();
foreach (var eEvent in eEvents)
{
var tuple = new RatingData()
{
Name = eEvent.Name, Data = new List <NameRating>()
};
var eventConferences = conferences.Where(c => c.Id == eEvent.ConferenceId);
foreach (var conference in eventConferences)
{
var userConference = from ea in _context.EventRatings.Where(eu => eu.EventId == eEvent.Id)
join ce in conference.Events on ea.EventId equals ce.Id
where ea.EventId == ce.Id select new
{
ea.UserId,
ea.Rating,
ce.ConferenceId
};
var conferenceRating = userConference.GroupBy(uc => uc.ConferenceId).ToList().Select(group => new IdRating()
{
Id = @group.Key,
Rating = @group.Sum(i => i.Rating) / Math.Max(@group.Count(), 1)
});
var rating = conferenceRating.FirstOrDefault(ca => ca.Id == conference.Id);
if (output.Any(o => o.Name == eEvent.Name))
{
output.First(o => o.Name == eEvent.Name).Data.Add(rating == null
? new NameRating()
{
Name = conference.Edition, Rating = 0
}
: new NameRating()
{
Name = conference.Edition, Rating = rating.Rating
});
}
else
{
tuple.Data.Add(rating == null
? new NameRating()
{
Name = conference.Edition, Rating = 0
}
: new NameRating()
{
Name = conference.Edition, Rating = rating.Rating
});
}
}
output.Add(tuple);
}
return(output.ConvertAll(JsonConvert.SerializeObject));
}
public RatingData CalculateRawRating()
{
return(RatingData.Accumulate(allSentences.Select(item => item.CalculateRating())));
}
///
public override void Train()
{
external_scores = RatingData.Read(PredictionFile, UserMapping, ItemMapping);
// we dont use it locally but it should be initialized before entering the parallel code
IList <IList <int> > nonsense = external_scores.ByUser;
}
public ProductTypes.Rating Merge(ProductTypes.Rating src, RatingData update)
{
return update == null ? src : Convert(update);
}