- python 3.6
- sklearn
- pandas
- tensorflow 1.8.0
- keras 2.1.6
-
K-Nearest Neighbor (KNN)
-
Support Vector Machine (SVM)
-
Gaussian Multinomial Naive Bayes (MultinomialNB)
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Decision Tree
-
Random Forest
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Extra Tree
-
Logistic Regression
-
KNN based Bagging
-
Logistic Regression
-
Majority Voting Ensemble Machine
-
Neural network
classifers | val acc |
---|---|
KNN | 85.55 |
AdaBoost | 42.20 |
LogisticRegression | 88.57 |
DecisionTree | 89.36 |
ExtraTrees | 96.12 |
KNeighbors | 82.96 |
Majority_Voting | 93.39 |
Naive_Bayes | 59.31 |
RandomForest | 96.33 |
LinearSVC | 94.53 |
Neural network | 99.22 |
use first two batches to train && use the last eight batchse to test the results
train accuracy : 0.5200065461091564
cross validation acc : 0.5200065461091564
batch id: 3 acc: 0.8284993694829761
batch id: 4 acc: 0.6024844720496895
batch id: 5 acc: 0.8629441624365483
batch id: 6 acc: 0.65
batch id: 7 acc: 0.49986161084970937
batch id: 8 acc: 0.20408163265306123
batch id: 9 acc: 0.5127659574468085
batch id: 10 acc: 0.32555555555555554
- 传感器特征的构成
- 数据集的每个传感器的8个维度特征大小是不一样的,所以现在的归一化方式存在问题
1 9 17....
2 10 18 ...
......
8 16 24 ...
分开进行训练