public void UD(int nbUsers, int numberTrainingExamples, int normalisation) {
List<List<int[][]>> usersConfusionMatrixes = new ArrayList<List<int[][]>>();
for (int user = 1; user <= nbUsers; user++) {
List<int[][]> userConfusionMatrixes = new ArrayList<int[][]>();
for (int knn = 0; knn < numberTrainingExamples; knn++)
userConfusionMatrixes.add(new int[10][10]);
usersConfusionMatrixes.add(userConfusionMatrixes);
}
String[] alphabet = {"0", "1", "2", "3", "4", "5", "6", "7"};
ConditionalRecognizer cr = new ConditionalRecognizer(alphabet);
for (int user = 1; user <= nbUsers; user++)
for (int teIndex = 1; teIndex <= numberTrainingExamples; teIndex++)
cr.addTemplate(user + "", strings.get("" + user + "signature" + teIndex));
cr.compile(normalisation);
for (int knn = numberTrainingExamples; knn <= numberTrainingExamples; knn++) {
for (int user = 1; user <= nbUsers; user++)
for (int teIndex = numberTrainingExamples + 1; teIndex <= 30; teIndex++) {
String[] foundSigs =
cr.recognizeForAllKnn(strings.get(user + "signature" + teIndex), normalisation, knn);
for (int i = 0; i < foundSigs.length; i++) {
String foundSig = foundSigs[i];
confusionMatrixes.get(i)[user - 1][Integer.parseInt(foundSig) - 1]++;
usersConfusionMatrixes.get(user - 1).get(i)[user - 1][Integer.parseInt(foundSig) - 1]++;
}
}
System.out.println(
"norm="
+ normalisation
+ "|nte="
+ numberTrainingExamples
+ "|nbUsers="
+ nbUsers
+ " recognized");
}
for (int user = 1; user <= nbUsers; user++)
for (int knn = 0; knn < numberTrainingExamples; knn++)
userRecognitionRates[user - 1][knn] =
Utils.recognitionRate(usersConfusionMatrixes.get(user - 1).get(knn));
// tw.println("norm="+normalisation+"|nte="+numberTrainingExamples+"|user="******": recognition
// rate = "+Utils.recognitionRate(userConfusionMatrix));
}
public void UI(int user, int numberTrainingExamples, int normalisation) {
List<int[][]> userConfusionMatrixes = new ArrayList<int[][]>();
for (int knn = 0; knn < numberTrainingExamples; knn++)
userConfusionMatrixes.add(new int[10][10]);
for (int firstUserIndex = 1; firstUserIndex <= 10; firstUserIndex++) {
String[] alphabet = {"0", "1", "2", "3", "4", "5", "6", "7"};
ConditionalRecognizer cr = new ConditionalRecognizer(alphabet);
for (int digitIndex = 0; digitIndex < 10; digitIndex++) {
int mod = 0;
int threshold = firstUserIndex + numberTrainingExamples;
for (int otherUser = firstUserIndex; mod * 10 + otherUser < threshold; otherUser++) {
if (otherUser == user) {
if (otherUser == 10) {
otherUser = 1;
mod = 1;
} else otherUser++;
threshold++;
}
cr.addTemplate(
Utils.intToDigit(digitIndex) + "",
strings.get("" + otherUser + Utils.intToDigit(digitIndex) + "1"));
if (otherUser == 10) {
otherUser = 0;
mod = 1;
}
}
}
cr.compile(normalisation);
for (int knn = numberTrainingExamples; knn <= numberTrainingExamples; knn++) {
for (int digitIndex = 0; digitIndex < 10; digitIndex++) {
for (int teIndex = 1; teIndex <= 10; teIndex++) {
String[] foundDigits =
cr.recognizeForAllKnn(
strings.get("" + user + Utils.intToDigit(digitIndex) + teIndex),
normalisation,
knn);
for (int i = 0; i < foundDigits.length; i++) {
String foundDigit = foundDigits[i];
confusionMatrixes.get(i)[digitIndex][Utils.digitToInt(foundDigit)]++;
userConfusionMatrixes.get(i)[digitIndex][Utils.digitToInt(foundDigit)]++;
}
System.out.println(
"norm="
+ normalisation
+ "|nte="
+ numberTrainingExamples
+ "|user="******"|fui="
+ firstUserIndex
+ "|char="
+ Utils.intToDigit(digitIndex)
+ " recognized");
}
}
}
}
for (int knn = 0; knn < numberTrainingExamples; knn++)
userRecognitionRates[user - 1][knn] = Utils.recognitionRate(userConfusionMatrixes.get(knn));
}
