Commit 52494095 authored by PauTheu's avatar PauTheu
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parent 48015cb6
...@@ -27,4 +27,12 @@ The best validation result can be observed for CNNs with depth-wise separable co ...@@ -27,4 +27,12 @@ The best validation result can be observed for CNNs with depth-wise separable co
To tackle the concept drift problematic occuring in the testset, we combine several neural models into one ensemble. To tackle the concept drift problematic occuring in the testset, we combine several neural models into one ensemble.
Each of the models is trained on a single region of wind turbines. Each of the models is trained on a single region of wind turbines.
The models' predictions are combined by using a weighted majority vote. The models' predictions are combined by using a weighted majority vote.
More specifically, the models' output probabilities are acquired via softmax and averaged to form the ensemble's output. More specifically, the models' output probabilities are acquired via softmax and averaged to form the ensemble's output.
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## `Others.ipynb`
Data: use ten best features explored in data_exploration.ipynb file
### Approaches:
1. Lightgbm: leaf wise tree growth (best first) instead of level wise tree growth. low acc.
2. Easy NN: 2 hidden layers, batches 64, epochs 50, binary classification, Relu, ADAM. low acc.
3. TPOPT: looks for the best classification pipeline. low acc.
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