wanling_tsai_exp_dataset

This dataset contains four collections of samples stored in NumPy .npy format, designed for binary classification tasks. Each dataset folder includes two subfolders, train\/ and test\/, which further contain two class files (class0.npy and class1.npy). Each .npy file stores a 2D array, where every row represents a single data sample. The training and testing splits are explicitly separated, allowing direct use in machine learning workflows without additional preprocessing.The dataset is particularly suitable for evaluating data augmentation, data generation, and decision boundary analysis methods, as it provides well-structured binary-labeled data. Researchers can easily load the files using Python and NumPy, then apply machine learning models such as neural networks, support vector machines, or other classification algorithms.By providing a clean and standardized format, this dataset enables efficient experimentation in binary classification tasks, supports reproducibility in research, and can serve as a benchmark resource for future studies in machine learning and data augmentation.