CACP is made for comparing newly developed classification algorithms (both traditional and incremental) in Python with other commonly used classifiers to evaluate classification performance, ...

Compare metrics such as f1 score and confusion matrices for your machine learning models and through voting or stacking them, then predict on test data with your choice of voting or stacking! This ...

Abstract: The pervasiveness of neural networks (NNs) in critical computer vision and image processing applications makes them very attractive for adversarial manipulation. A large body of existing ...