public Map<Match, Map<String, Map<Object, Double>>> predictMatches(Match[] matches) throws Exception { Map<Match, Map<String, Map<Object, Double>>> retval = new TreeMap<Match, Map<String, Map<Object, Double>>>(); LinkedList<Match> nMatches = new LinkedList<Match>(); for (Match match : matches) { if (teams.get(match.country, match.home) != null && teams.get(match.country, match.away) != null) nMatches.add(match); } matches = new Match[nMatches.size()]; int i = 0; for (Match match : nMatches) { matches[i] = match; i++; } for (Match match : matches) { try { Map<String, Map<Object, Double>> toPut = new TreeMap<String, Map<Object, Double>>(); // Match to predict double[] toPredict = this.getKamp(match.home, match.away, match.country); // Dataset to use List<DataEntry> trainingset = this.getTrainingSet(match.country, match.division); if (Setup.NORMALIZE_DATA) { Normalizer norm = this.normalizers.get(this.getDataKey(match.country, match.division)); norm.apply(toPredict); } // The classification // Find number of neighbours int neighbours = 10; // Default try { neighbours = getBestKForNearestNeighbour(match.country, match.division); } catch (SQLException e1) { Log.e(e1); } // Find kernel Estimator est = null; try { est = getBestKernelForNaiveBayes(match.country, match.division); } catch (SQLException e1) { Log.e(e1); } toPut.put("lda", this.predictMatchLDA(trainingset, toPredict)); toPut.put("nb", this.predictMatchNB(trainingset, toPredict, est)); toPut.put("nn", this.predictMatchNN(trainingset, toPredict, neighbours)); retval.put(match, toPut); } catch (Exception e) { Log.e(e); } } return retval; }
public synchronized void load() throws SQLException { // And calculate Connection connection = getDb(); Statement stmt = connection.createStatement(); ResultSet scoreSet = stmt.executeQuery("SELECT hold,division,land from klubber"); while (scoreSet.next()) { // Fetch info String land = scoreSet.getString("land"); String hold = scoreSet.getString("hold"); int division = scoreSet.getInt("division"); double rating = Setup.pointStart / (Math.pow(Setup.divisionsforskel, division)); Team team = new Team(hold, land, division, rating, Setup.matchesToStore); teams.addTeam(team); } stmt.close(); // Load the matches stmt = connection.createStatement(); String matchesSQL = "SELECT * FROM kampe order by dato asc"; ResultSet r = stmt.executeQuery(matchesSQL); while (r.next()) { try { // Fetch info String country = r.getString("land"); Team away = teams.get(country, r.getString("udehold")); int division = r.getInt("division"); int goalsAway = r.getInt("udemaal"); int goalsHome = r.getInt("hjemmemaal"); String seasonStartYear = r.getString("season_start_year"); Team home = teams.get(country, r.getString("hjemmehold")); int round = r.getInt("runde"); Kamp match = new Kamp(home, away, goalsHome, goalsAway, round, seasonStartYear); // Find result Udfald y = null; if (goalsHome > goalsAway) y = Udfald.HJEMME; else if (goalsHome == goalsAway) y = Udfald.UAFGJORT; else y = Udfald.UDE; double[] features = getKamp(home, away, country); DataEntry matchInfo = new DataEntry(features, y); matchInfo.addExtra("season_start_year", seasonStartYear); String key = getDataKey(country, division + ""); synchronized (this) { LinkedList<DataEntry> matchData = dataset.get(key); if (matchData == null) { matchData = new LinkedList<DataEntry>(); dataset.put(key, matchData); } // If enough matches and so on, update if (home.totalplayed >= Setup.TRAINING_ROUNDS && away.totalplayed >= Setup.TRAINING_ROUNDS // Total played at least && round >= Setup.antalRunder // Total played in start of each season ) { matchData.add(matchInfo); } } // And update a lot of information // Skal altid ske. Til træning af klubbernes point teams.opdaterPoint(home, away, goalsHome, goalsAway, division); // The rest home.addLatestHomeMatch(match); home.addLatestMatch(match); away.addLatestAwayMatch(match); away.addLatestMatch(match); home.addInternal(match); away.addInternal(match); home.totalplayed++; away.totalplayed++; } catch (Exception e) { Log.e(e); } } r.close(); stmt.close(); // Filter out noise if needed if (Setup.FILTER_DATA) { for (String key : dataset.keySet()) { LinkedList<DataEntry> matches = dataset.get(key); Setup.FILTER_HANDLER.applyFilters(matches); } } // Prepare normalizer for (String key : dataset.keySet()) { Normalizer normalizer = new Normalizer(dataset.get(key), Normalizer.Method.NORMALIZATION); normalizers.put(key, normalizer); if (Setup.NORMALIZE_DATA) normalizer.apply(dataset.get(key)); } }