Genetic Variant Classification Machine Learning Pipeline

Develop a comprehensive machine learning pipeline using scikit-learn and TensorFlow for classifying genetic variants associated with rare genetic disorders. Create a feature engineering workflow that can process genomic data from VCF files, implement multiple classification algorithms (Random Forest, SVM, Neural Networks), and design a model evaluation system that calculates clinical significance scores. Include cross-validation strategies specific to genetic variant analysis and a reporting mechanism for model uncertainty.