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Added temp results from README, added more hyperparameter runs and added temporal results to presentation

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Tuan-Dat Tran 2021-06-08 21:50:31 +00:00
parent 60a48ce49c
commit 33941658b9
3 changed files with 312 additions and 18 deletions
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1-first-project/Slides/IUI_MP1_Presentation-1.pptx
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1-first-project/tdt/Hyperparameter.ipynb
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@ -891,7 +891,55 @@
" Dense Count 1: 2\n", " Dense Count 1: 2\n",
" Dense Neurons 1: 1800\n", " Dense Neurons 1: 1800\n",
" Dense Count 2: 3\n", " Dense Count 2: 3\n",
" Dense Neurons 2: 1200\n" " Dense Neurons 2: 1200\n",
"Accuracy: 78.40\n",
"Testing with: Threshold: 70\n",
" Leeway: 0\n",
" Epoch: 20\n",
" Dense Count 1: 2\n",
" Dense Neurons 1: 1800\n",
" Dense Count 2: 3\n",
" Dense Neurons 2: 1800\n",
"Accuracy: 78.09\n",
"Testing with: Threshold: 70\n",
" Leeway: 0\n",
" Epoch: 20\n",
" Dense Count 1: 2\n",
" Dense Neurons 1: 1800\n",
" Dense Count 2: 3\n",
" Dense Neurons 2: 2400\n",
"Accuracy: 77.56\n",
"Testing with: Threshold: 70\n",
" Leeway: 0\n",
" Epoch: 20\n",
" Dense Count 1: 2\n",
" Dense Neurons 1: 2400\n",
" Dense Count 2: 1\n",
" Dense Neurons 2: 600\n",
"Accuracy: 78.10\n",
"Testing with: Threshold: 70\n",
" Leeway: 0\n",
" Epoch: 20\n",
" Dense Count 1: 2\n",
" Dense Neurons 1: 2400\n",
" Dense Count 2: 1\n",
" Dense Neurons 2: 1200\n",
"Accuracy: 78.49\n",
"Testing with: Threshold: 70\n",
" Leeway: 0\n",
" Epoch: 20\n",
" Dense Count 1: 2\n",
" Dense Neurons 1: 2400\n",
" Dense Count 2: 1\n",
" Dense Neurons 2: 1800\n",
"Accuracy: 78.24\n",
"Testing with: Threshold: 70\n",
" Leeway: 0\n",
" Epoch: 20\n",
" Dense Count 1: 2\n",
" Dense Neurons 1: 2400\n",
" Dense Count 2: 1\n",
" Dense Neurons 2: 2400\n"
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1-first-project/tdt/README.md
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@ -74,6 +74,7 @@ This segment are notes dedicated to the neural network itself.
```python ```python
thresh = 100 thresh = 100
leeway = 5 leeway = 5
epoch = 20
model = Sequential() model = Sequential()
@ -102,6 +103,7 @@ Evaluate on test data
```python ```python
thresh = 75 thresh = 75
leeway = 3 leeway = 3
epoch = 20
model = Sequential() model = Sequential()
@ -130,6 +132,7 @@ Evaluate on test data
```python ```python
thresh = 10 thresh = 10
leeway = 3 leeway = 3
epoch = 20
model = Sequential() model = Sequential()
@ -153,11 +156,12 @@ Evaluate on test data
82/82 [==============================] - 0s 2ms/step - loss: 2.5231 - acc: 0.3696 82/82 [==============================] - 0s 2ms/step - loss: 2.5231 - acc: 0.3696
``` ```
#### Test4 (71.51%) #### Test4 (69.66%)
```python ```python
thresh = 50 thresh = 50
leeway = 3 leeway = 3
epoch = 20
model = Sequential() model = Sequential()
@ -178,7 +182,249 @@ model.add(Dense(26, activation='softmax'))
``` ```
Evaluate on test data Evaluate on test data
82/82 [==============================] - 0s 2ms/step - loss: 1.5005 - acc: 0.7151 82/82 [==============================] - 0s 2ms/step - loss: 1.6965 - acc: 0.6966
``` ```
#### Test5 ()
#### Test5 (73.13%)
```python
thresh = 60
leeway = 3
epoch = 20
model = Sequential()
model.add(Flatten(input_shape=X_filter[0].shape))
model.add(BatchNormalization())
model.add(Dense(1560, activation='relu'))
model.add(Dense(750, activation='relu'))
model.add(Dense(300, activation='relu'))
model.add(Dense(156, activation='relu'))
model.add(Dense(26, activation='softmax'))
```
```
Evaluate on test data
82/82 [==============================] - 0s 2ms/step - loss: 1.4886 - acc: 0.7313
```
#### Test6 (75.68%)
```python
thresh = 68
leeway = 3
epoch = 20
model = Sequential()
model.add(Flatten(input_shape=X_filter[0].shape))
model.add(BatchNormalization())
model.add(Dense(1560, activation='relu'))
model.add(Dense(750, activation='relu'))
model.add(Dense(300, activation='relu'))
model.add(Dense(156, activation='relu'))
model.add(Dense(26, activation='softmax'))
```
```
Evaluate on test data
82/82 [==============================] - 0s 2ms/step - loss: 1.4227 - acc: 0.7568
```
#### Test7 (76.07%)
```python
thresh = 68
leeway = 3
epoch = 30
model = Sequential()
model.add(Flatten(input_shape=X_filter[0].shape))
model.add(BatchNormalization())
model.add(Dense(1560, activation='relu'))
model.add(Dense(750, activation='relu'))
model.add(Dense(300, activation='relu'))
model.add(Dense(156, activation='relu'))
model.add(Dense(26, activation='softmax'))
```
```
Evaluate on test data
82/82 [==============================] - 0s 2ms/step - loss: 1.5863 - acc: 0.7607
```
#### Test8 (75.49%)
```python
THRESH = 70
LEEWAY = 3
EPOCH = 30
DENSE_COUNT = 5
DENSE_NEURONS = 1800
```
```
Evaluate on test data
21/21 [==============================] - 0s 2ms/step - loss: 1.5598 - acc: 0.7684
```
#### Test9 (78.15%)
```python
THRESH = 70
LEEWAY = 1
EPOCH = 30
DENSE_COUNT = 5
DENSE_NEURONS = 1800
```
```
Evaluate on test data
21/21 [==============================] - 0s 2ms/step - loss: 1.4677 - acc: 0.7815
```
#### Test10 (77.64%)
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 5
DENSE_NEURONS = 1900
```
#### Test11 (77.41%)
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 5
DENSE_NEURONS = 1800
```
#### Test12 (73.90%)
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 5
DENSE_NEURONS = 1800
DENSE_COUNT = 5
DENSE_NEURONS = 900
```
#### Test13 (78.89%)
NORM->FLAT->DENSE
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 5
DENSE_NEURONS = 1900
```
#### Test14 (79.04%)
NORM->FLAT->DENSE
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 5
DENSE_NEURONS = 1800
```
#### Test15 (79.00%)
NORM->FLAT->DENSE
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 5
DENSE_NEURONS = 1700
```
#### Test16 (78.69%)
NORM->FLAT->DENSE
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 5
DENSE_NEURONS = 1600
```
#### Test17 (78.57%)
NORM->FLAT->DENSE
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 4
DENSE_NEURONS = 1800
```
#### Test18 (78.12%)
NORM->FLAT->DENSE
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 6
DENSE_NEURONS = 1800
```
#### Test19 (79.13%)
NORM->FLAT->DENSE
```python
THRESH = 70
LEEWAY = 0
EPOCH = 30
DENSE_COUNT = 3
DENSE_NEURONS = 1800
DENSE2_COUNT = 2
DENSE2_NEURONS = 1200
```