# full_mn10_as_2s_seed42_group-source

model=`mn10_as` head=`mlp` sr=32000 clip=2.0s epochs=20 folds=5 seed=42

## Held-out test metrics by fold

| fold | test_acc | test_balanced_acc | test_macro_precision | test_macro_recall | test_macro_f1 |
|---|---|---|---|---|---|
| 1 | 0.9709 | 0.9682 | 0.9683 | 0.9682 | 0.9677 |
| 2 | 0.9909 | 0.9903 | 0.9906 | 0.9903 | 0.9904 |
| 3 | 0.9836 | 0.9817 | 0.9830 | 0.9817 | 0.9819 |
| 4 | 0.9800 | 0.9794 | 0.9778 | 0.9794 | 0.9786 |
| 5 | 0.9617 | 0.9618 | 0.9594 | 0.9618 | 0.9592 |

## Mean / std across folds

| metric | mean | std | min | max |
|---|---|---|---|---|
| test_acc | 0.9774 | 0.0113 | 0.9617 | 0.9909 |
| test_balanced_acc | 0.9763 | 0.0113 | 0.9618 | 0.9903 |
| test_macro_precision | 0.9758 | 0.0123 | 0.9594 | 0.9906 |
| test_macro_recall | 0.9763 | 0.0113 | 0.9618 | 0.9903 |
| test_macro_f1 | 0.9756 | 0.0122 | 0.9592 | 0.9904 |

## Best fold (fold 2, by `test_macro_recall`) — per-class

| label | precision | recall | f1 | support |
|---|---|---|---|---|
| baby_cry | 0.9954 | 0.9954 | 0.9954 | 216.0000 |
| bicycle | 1.0000 | 1.0000 | 1.0000 | 98.0000 |
| glass_break | 1.0000 | 0.9741 | 0.9869 | 116.0000 |
| gunshot | 0.9672 | 0.9916 | 0.9793 | 119.0000 |
| macro avg | 0.9906 | 0.9903 | 0.9904 | 549.0000 |
| weighted avg | 0.9911 | 0.9909 | 0.9909 | 549.0000 |

## Best fold (fold 2) — confusion matrix

행=실제(true), 열=예측(pred)

| true \ pred | baby_cry | bicycle | glass_break | gunshot |
|---|---|---|---|---|
| baby_cry | 215 | 0 | 0 | 1 |
| bicycle | 0 | 98 | 0 | 0 |
| glass_break | 0 | 0 | 113 | 3 |
| gunshot | 1 | 0 | 0 | 118 |

## Per-class recall across all folds

| fold | baby_cry | bicycle | glass_break | gunshot |
|---|---|---|---|---|
| fold_01 | 0.9861 | 0.9898 | 0.9138 | 0.9832 |
| fold_02 | 0.9954 | 1.0000 | 0.9741 | 0.9916 |
| fold_03 | 0.9954 | 1.0000 | 0.9397 | 0.9916 |
| fold_04 | 0.9861 | 1.0000 | 0.9569 | 0.9748 |
| fold_05 | 0.9676 | 1.0000 | 0.8966 | 0.9832 |
| mean | 0.9861 | 0.9980 | 0.9362 | 0.9849 |
| std | 0.0113 | 0.0046 | 0.0314 | 0.0070 |

## Pooled confusion matrix (all 5 folds, n=2745)

행=실제(true), 열=예측(pred)

| true \ pred | baby_cry | bicycle | glass_break | gunshot |
|---|---|---|---|---|
| baby_cry | 1065 | 0 | 4 | 11 |
| bicycle | 0 | 489 | 1 | 0 |
| glass_break | 0 | 1 | 543 | 36 |
| gunshot | 4 | 0 | 5 | 586 |