The prediction of audit opinions of listed companies plays a significant role in the security market risk prevention. By introducing machine learning methods, many innovations can be implemented to improve audit quality, lift audit efficiency, and cultivate the keen insight of auditors. However, in a realistic environment, category imbalance and critical feature selection exist in the prediction model of company audit opinions. This paper firstly combines batched sparse principal component analysis (BSPCA) with kernel fuzzy clustering algorithm...