CHANGELOG¶

v0.10 (29/10/2019)¶

#535 Added new package secml.explanation, which provides different methods for explaining machine learning models. See documentation and examples for more information.
#584 [beta] Added CModelCleverhans and CAttackEvasionCleverhans to support adversarial attacks from CleverHans, a Python library to benchmark vulnerability of machine learning systems to adversarial examples.

#565 Added new abstract interface CClassifierDNN from which new classes implementing Deep Neural Networks can inherit.
#555 Added CNormalizerDNN, which allows using a CClassifierDNN as a preprocessor.
#593 Added CDataLoaderTorchDataset, which allows converting a torchvision dataset into a CDataset.
#598 Added gradient method for CKernelHistIntersection.

#562 Extended support of CClassifierPyTorch to nested PyTorch modules.
#594 CClassifierPyTorch.load_model() is now able to also load models trained with PyTorch (without using our wrapper). New parameter classes added to the method to match classes to indexes in the loaded model.
#579 Left side single row/column broadcast is now supported for sparse vs sparse CArray operations.
#582 Improved performance of CNormalizerMeanStd when multiple channels are defined.
#576 Vastly improved the performance of kernels by removing loops over samples in many classes and refactoring main routines.
#562 Improved grad_f_x computation at a specific layer in CClassifierPyTorch.

#578 CClassifierPyTorch now inherits from CClassifierDNN. The following changed accordingly: parameter torch_model renamed to model; property layer_shapes is now defined; method save_checkpoint removed.
#562 Parameter layer of CClassifierPyTorch.get_layer_output() is now renamed layer_names as a list of layers names is supported (a single layer name is still supported as input). A dictionary is returned if multiple layers are requested. See the documentation for more information.
#533 Double initialization in CAttackEvasionPGDLS will now be executed regardless of the classifier type (linear or nonlinear) if the double_init parameter of .run() method is set to True.
#591 It is now not required to call the fit method of CNormalizerMeanSTD if fixed mean/std values are used.

#561 Fixed CConstraintBox not always applied correctly for float data.
#577 Fixed CClassifierPyTorch.decision_function applying preprocess twice.
#581 Fixed gradient computation of CKernelChebyshevDistance.
#599 Kernels using distances are now based on negative distances (to correctly represent similarity measures). Affected classes are: CKernelChebyshevDistance, CKernelEuclidean.

#561 Removed parameter precision from CConstraint.is_violated().
#575 Parameter batch_size of CKernel is now deprecated.
#597 Removed unused parameter gamma from CKernelChebyshevDistance.
#596 Removed CKernelHamming.
#602 Renamed CNormalizerMeanSTD to CNormalizerMeanStd. The old class has been deprecated and will be removed in a future vearsion.

#538 Added a notebook tutorial on the use of Explainable ML methods provided by the secml.explanation package.
#573 Improved visualization of attack results in 07-ImageNet tutorial.
#610 Fixed spacing between parameter and parameter type in the docs.
#605 Fixed documentation of classes requiring extra components not being displayed.
#608 Added acknowledgments to README.

#536 Added CClassifierPytorch to support Neural Networks (NNs) through PyTorch deep learning platform.

#554 Fixed CClassifierSkLearn.predict() not working when using pretrained sklearn models.

#559 Deprecated functions and classes are now correctly visualized in the documentation.
#560 Updated development roadmap accordingly to 0.10, 0.11 and 0.12 releases.

#532 Method CPreProcess.revert() is deprecated. Use .inverse_transform() instead.
#552 CClassifierKDE is now deprecated. Use CClassifierSkLearn with sklearn.neighbors.KernelDensity instead.
#553 CClassifierMCSLinear is now deprecated. Use CClassifierSkLearn with sklearn.ensemble.BaggingClassifier instead.

This version does not contain any significant change.