public static InstanceList scale(InstanceList trainingList, double lower, double upper) {
InstanceList ret = copy(trainingList);
Alphabet featDict = ret.getDataAlphabet();
double[] feat_max = new double[featDict.size()];
double[] feat_min = new double[featDict.size()];
for (int i = 0; i < feat_max.length; i++) {
feat_max[i] = -Double.MAX_VALUE;
feat_min[i] = Double.MAX_VALUE;
}
for (int i = 0; i < ret.size(); i++) {
Instance inst = ret.get(i);
FeatureVector fv = (FeatureVector) inst.getData();
for (int loc = 0; loc < fv.numLocations(); loc++) {
int featId = fv.indexAtLocation(loc);
double value = fv.valueAtLocation(loc);
double maxValue = feat_max[featId];
double minValue = feat_min[featId];
double newMaxValue = Math.max(value, maxValue);
double newMinValue = Math.min(value, minValue);
feat_max[featId] = newMaxValue;
feat_min[featId] = newMinValue;
}
}
// double lower = -1;
// double upper = 1;
for (int i = 0; i < ret.size(); i++) {
Instance inst = ret.get(i);
FeatureVector fv = (FeatureVector) inst.getData();
for (int loc = 0; loc < fv.numLocations(); loc++) {
int featId = fv.indexAtLocation(loc);
double value = fv.valueAtLocation(loc);
double maxValue = feat_max[featId];
double minValue = feat_min[featId];
double newValue = Double.NaN;
if (maxValue == minValue) {
newValue = value;
} else if (value == minValue) {
newValue = lower;
} else if (value == maxValue) {
newValue = upper;
} else {
newValue = lower + (upper - lower) * (value - minValue) / (maxValue - minValue);
}
fv.setValueAtLocation(loc, newValue);
}
}
return ret;
}
