Recently, works on integrating HTM with STM, called hybrid transactional memory (HyTM), have intensively studied. However, the existing works consider only the prediction of a conflict between two transactions and provide a static HTM configuration for all workloads. To solve the problems, we proposes a hybrid transactional memory scheme based on both abort prediction and an adaptive retry policy, called HyTM-AP. First, our HyTM-AP can predict not only conflicts between concurrently running transactions, but also the capacity and other aborts of transactions by collecting the information of transactions previously executed. Second, our HyTM-AP can provide an adaptive retry policy based on machine learning algorithms, according to the characteristic of a given workload. Finally, through our experimental performance analysis using the STAMP benchmark, our HyTM-AP shows 12~13% better performance than the existing HyTM schemes.