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));
}
}