Adaptive Machine Learning Feature Selection for Complex Datasets

Create an intelligent feature selection framework for scientific datasets that can automatically identify, rank, and validate potential predictive features across multiple domains. The system should support unsupervised and supervised learning techniques, provide statistical significance testing, and generate interpretable feature importance visualizations. Include support for handling high-dimensional, sparse, and noisy scientific datasets.