static void Main(string[] args)
{
string errorMessage = "";
if (!File.Exists(MovieTitlesPath))
{
errorMessage += $"Failed to find file ${MovieTitlesPath} - please update variable ${nameof(MovieTitlesPath)} or create that file.\n";
}
if (!File.Exists(UserRatingsTrainingPath))
{
errorMessage += $"Failed to find file ${UserRatingsTrainingPath} - please update variable ${nameof(UserRatingsTrainingPath)} or create that file.\n";
}
if (!File.Exists(UserRatingsTestPath))
{
errorMessage += $"Failed to find file ${UserRatingsTestPath} - please update variable ${nameof(UserRatingsTestPath)} or create that file.\n";
}
if (errorMessage != "")
{
Console.ForegroundColor = ConsoleColor.Red;
Console.WriteLine("Not all files available - not running!");
Console.WriteLine(errorMessage);
Console.ResetColor();
Console.WriteLine("Press any key to continue...");
Console.ReadKey();
return;
}
var startTime = DateTime.Now;
Console.WriteLine(startTime);
Console.WriteLine("Parsing the input files...");
Dictionary <int, string> movieTitles = CsvParserUtils.ParseCsvAsList <Movie>(MovieTitlesPath).ToDictionary(n => n.MovieId, n => n.Title);
UserCache trainingSetCache = UserCache.BuildUserCache(UserRatingsTrainingPath);
UserCache testingSetCache = UserCache.BuildUserCache(UserRatingsTestPath);
Console.WriteLine("Initializing predictors...");
PearsonCoefficientCalculator pearsonCalculator = new PearsonCoefficientCalculator(trainingSetCache);
MovieScorePredictor predictor = new MovieScorePredictor(pearsonCalculator);
// NOTE: feel free to comment out any of the lines below depending on what you want to execute
MakePredictionsOnTestFileAndCalculateError(predictor, testingSetCache);
MakeMovieRecommendationsForUser999999InTrainingSet(predictor, trainingSetCache, movieTitles);
var endTime = DateTime.Now;
Console.WriteLine(endTime);
var totalMinutes = (endTime - startTime).TotalMinutes;
Console.WriteLine("Took {0} minutes.", totalMinutes);
Console.WriteLine("Press any key to quit...");
Console.ReadKey();
}
// For recommendations, the following movies were used
//17622, 999999, 5.0
//10362, 999999, 5.0
//5448, 999999, 5.0
//14, 999999, 4.0
//21, 999999, 1.0
//69, 999999, 2.0
//68, 999999, 4.0
//209, 999999, 1.0
//215, 999999, 5.0
//731, 999999, 1.0
//6205, 999999, 5.0
//12293, 999999, 5.0
//12298, 999999, 1.0
//12311, 999999, 1.0
//12954, 999999, 1.0
//11726, 999999, 5.0
//13501, 999999, 5.0
//13595, 999999, 1.0
//13617, 999999, 1.0
//13638, 999999, 2.0
//7624, 999999, 4.0
// NOTE: Only used for testing
private void RunLocalTests(MovieScorePredictor predictor)
{
List <UserRating> testingUserRatings = CsvParserUtils.ParseCsvAsList <UserRating>(UserRatingsTestPath);
double prediction = predictor.PredictScore(testingUserRatings[0].UserId, testingUserRatings[0].MovieId);
UserCache testingSetCache = UserCache.BuildUserCache(UserRatingsTestPath);
var allScores = predictor.PredictAllScores(testingUserRatings[0].UserId,
testingSetCache.GetUserMovieRatings(testingUserRatings[0].UserId), K);
var allErrors = new List <double>();
foreach (var keyValuePair in allScores)
{
var realScore = testingSetCache.GetUserMovieRatings(testingUserRatings[0].UserId)[keyValuePair.Key];
double error = Math.Abs(keyValuePair.Value.Prediction - realScore);
allErrors.Add(error);
}
}
public static UserCache BuildUserCache(string path)
{
List <UserRating> trainingUserRatings = CsvParserUtils.ParseCsvAsList <UserRating>(path);
return(new UserCache(trainingUserRatings));
}