A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification

The code supports replication of results on TCGA Pan-cancer and BRCA datasets and includes data preprocessing, model training, and evaluation scripts: Python scripts for data preprocessing and integration Autoencoder implementation for multimodal feature learningHybrid ensemble training code (DL/ML models and meta-learner)PSO and backpropagation hybrid optimization codeParallel execution scriptsInstructions for replicating results on TCGA Pan-cancer and BRCA datasets