Merge branch 'release/release-0.2'

dsmilab · Aug 7, 2018 · 63c428d · 63c428d
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diff --git a/.gitignore b/.gitignore
@@ -8,3 +8,15 @@ data/
 ipynb/\.ipynb_checkpoints/
 
 ipynb/__pycache__/
+
+util/taiko/__pycache__/
+
+util/taiko/image/__pycache__/
+
+util/taiko/io/__pycache__/
+
+util/taiko/tools/__pycache__/
+
+util/taiko/preprocessing/__pycache__/
+
+util/\.ipynb_checkpoints/
diff --git a/README.md b/README.md
@@ -11,8 +11,15 @@ In general, follow the paper [Motion Primitive-Based Human Activity Recognition
 
 ![](docs/flowchart.png)
 
+<br/>
+
+## Preview
+
+### Collect Data
+
 Belows are repos for collecting raw data from wearable devices.
 
+
 1. [beagle_bone_blue_data_acq](https://github.com/taoyilee/beagle_bone_blue_data_acq)
 
 	- [Introduction of beaglebone-blue](docs/144934_data.pdf): The official manual of BBB.
@@ -25,32 +32,103 @@ Belows are repos for collecting raw data from wearable devices.
 
 <br/>
 
-## Experiment
+### Singal anaimation
+
 Belows two animations are some extraced features with the specific entire play, and we plot vertical color lines to represent real true hit event. 
 
 ![](docs/0420-axyz.gif)
 ![](docs/0420-gxyz.gif)
 
+<br/>
+
+### Event schematic diagram
+
 We can interpret the local event as the following figure.
 ![](docs/time_series_sense.png)
 
+<br/>
+
+## Experiment
+The followings are all about the song <font color='red'>**夢をかなえてドラえもん**</font>.
+
+<br/>
+
+### Classfication
+
+| hit event | hit event type  | origin hit type |
+|----------|:-------------:|------:|
+| *no* | 0 | 0 |
+| *single* | 1 | 1, 2, 3, 4 |
+| *stream* | 2 | 5, 6 |
+
+<br/>
+
+### Model
+
+1. [CNN](util/screenshot_model_generator.ipynb): train the score prediction model.
+
+2. [LGBM](util/doraemon_LGBM.ipynb): train the hit type classification model.
+
+<br/>
+
+### Observation
+
 More observation can be checked at the following notebooks.
 
-1. [EDA](util/taiko_feature_eda.ipynb): show the box plot of engineering features.
-2. [BoF](util/taiko_BoF.ipynb): show the traning error about the bag-of-features model.
-3. [Confusion Matrix](util/kernel_test.ipynb): use model to predict other performance.
 
-In addtion, [Taiko-Time-Series-Analytics](https://github.com/taoyilee/Taiko-Time-Series-Analytics) is another related repo analyzing this data.
+1. [Score Vis](util/score_visualization.ipynb): show all plays' score distributions.
+
+2. [Simple Analysis](util/doraemon_analysis.ipynb): briefly visualize training error for all drummers
+
+3. [Confusion Matrix](util/cm_test.ipynb): use model to predict other performance.
+
+In addition, [Taiko-Time-Series-Analytics](https://github.com/taoyilee/Taiko-Time-Series-Analytics) is another related repo analyzing this data.
 
 <br/>
 
 ## Result
-Use the last performance to train, we get
 
-![](docs/training_cnfm.png)
+### Confusion Matrix
+
+#### Case 1.
+
+Using <font color='blue'> **drummer 7** </font> 's 3th play to train and testing 1st, 2nd plays, respectively, then we get
+
+![](docs/test_cnfm-7-3to1.png)
+![](docs/test_cnfm-7-3to2.png)
+
+with the feature importance visualization 
+
+![](docs/feature_importance-7.png)
+
+#### Case 2.
+
+Using <font color='blue'> **drummer 4** </font> 's 3th play to train and testing 1st, 2nd plays, respectively, then we get
+
+![](docs/test_cnfm-4-3to1.png)
+![](docs/test_cnfm-4-3to2.png)
+
+with the feature importance visualization 
+
+![](docs/feature_importance-4.png)
+
+<br/>
+
+### Self-cross test
+
+Use # to train and # to valid and then test #.
+
+![](docs/barplot_all.png)
+
+Resampling causes increasing training error. On the other hand, scaling causes decreasing one, in general.
+
+<br/>
 
-However, predict a test performance, we get
+### All-cross test
 
-![](docs/test_cnfm.png)
+![](docs/heatmap_yy.png)
+![](docs/heatmap_yn.png)
+![](docs/heatmap_ny.png)
+![](docs/heatmap_nn.png)
 
-There is a long way to go! 
+Scaling makes decreasing training error. But resampling has no fixed result.
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