FelixNeutatz

Thank you, for your idea. I tried to use squared values, but there is still no significant improvement. You can find the implementation of your idea in the function costFunctionSumPow()

I get a similar error on Ubuntu ``` ython3.7/site-packages/numpy/core/include -c mdlp/_mdlp.cpp -o build/temp.linux-x86_64-3.7/mdlp/_mdlp.o In file included from /home/felix/FastFeatures/new_project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1822:0, from /home/felix/FastFeatures/new_project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12, from /home/felix/FastFeatures/new_project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4, from mdlp/_mdlp.cpp:539: /home/felix/FastFeatures/new_project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy...

Thank you so much! This is really helpful. Maybe this should go into the documentation :)

Hi @eddiebergman, thank you for the hint, I found that automl.get_models_with_weights() works: ``` #get_models_with_weights(): (0.56, SimpleClassificationPipeline({'balancing:strategy': 'weighting', 'classifier:__choice__': 'gradient_boosting', 'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'no_preprocessing', 'classifier:gradient_boosting:early_stop': 'train', 'classifier:gradient_boosting:l2_regularization': 8.789671314063565e-10, 'classifier:gradient_boosting:learning_rate': 0.19595673731599184, 'classifier:gradient_boosting:loss':...

Hi @beat-buesser, great to hear that you are already thinking in that direction. In a first prototype, I used [ScikitlearnLogisticRegression](https://github.com/Trusted-AI/adversarial-robustness-toolbox/blob/09262467e6f0a5832d2580b0bf995ecee333171d/art/estimators/classification/scikitlearn.py#L780) as a template to implement a quick-and-dirty ScikitlearnLinearRegression class and...

Hi @beat-buesser, I just quickly implemented the needed classes in a quick-and-dirty fashion in my current repository. Here, you can find the corresponding classes: [FastGradientMethod](https://github.com/BigDaMa/DFS/blob/master/new_project/fastsklearnfeature/test/test_robustness/FGM_Regression.py) [ScikitlearnRegressor](https://github.com/BigDaMa/DFS/blob/master/new_project/fastsklearnfeature/test/test_robustness/ScikitlearnRegressor.py) [ScikitlearnLinearRegression](https://github.com/BigDaMa/DFS/blob/master/new_project/fastsklearnfeature/test/test_robustness/LinearRegressionSKlearn.py) [Example](https://github.com/BigDaMa/DFS/blob/master/new_project/fastsklearnfeature/test/test_robustness/test_empirical_robustness_regresssion.py) Additionally, I...

alternatively, you can switch to an old version of scipy: python -m pip install scipy==0.18.1

I will be generated by running maven from this file: https://github.com/FelixNeutatz/parquet-flinktacular/blob/master/java/protobuf/commons/src/main/proto/addressbook.proto Best regards, Felix