HKDE-LACM: a hybrid model for lactic acid bacteria classification via k-mer and DNABERT-2 embedding fusion with cyclic DE-BO optimization

HKDE-LACM overcomes the limitations of traditional k-mer features by incorporating semantic embeddings, thereby enriching the representation of genomic sequences. In addition, the model can automatically identify optimal combinations of feature extractors and classifiers through the C-DBFA optimization framework. These advantages effectively enhance the model's generalization ability, making it a promising tool for genome-based LAB classification and related tasks.