void develop(
List<Instance> trn, List<Instance> tst, OnlineOptimizer op, int miniBatch, boolean sparse) {
DoubleIntPair best = new DoubleIntPair(0d, 0);
int yhat, count;
float[] scores;
String label;
double acc;
for (int epoch = 0; epoch < 50; epoch++) {
// training
count = 0;
for (Instance instance : trn) {
op.train(instance);
if (++count == miniBatch) {
op.updateMiniBatch();
count = 0;
}
}
if (count > 0) op.updateMiniBatch();
// evaluating
count = 0;
for (Instance instance : tst) {
scores = op.scores(instance.getFeatureVector());
yhat = MLUtils.argmax(scores);
label = op.getLabel(yhat);
if (instance.isStringLabel(label)) count++;
}
acc = MathUtils.accuracy(count, tst.size());
System.out.printf("%4d: %5.2f\n", epoch, acc);
if (best.d < acc) best.set(acc, epoch);
}
System.out.printf("best: %5.2f at %d epoch\n", best.d, best.i);
}
