A Novel Evaluating Model of CPV Vocational Ability Based on SVM Multilayer Classifier

The asset valuation is specialized work, and it requests the certified public valuer (CPV) to have the very strong specialized competent ability. Along with the development of the economic in China, the reform of stock system, the tax reform, and the application of fair value in new business accounting standards, the new evaluation domain develops unceasingly, and which sets the new request to the CPV vocational ability. Aiming at the problem of how to evaluate the CPV vocational ability, this paper proposes the multi-level classification evaluating model based on improved support vector machine (SVM), which uses the SVM classification combination in series and introduces the type weight factor and sample weight factor. The model not only solves the shortcomings of small sample, high dimension, nonlinear and local minima in the traditional model, but solves the wrong classification question caused by the number imbalance of training samples and data interference. The CPV vocational ability evaluating results of 12 asset valuation companies in Hebei Province show that the model is simple and feasible, and improve the evaluating accuracy and efficiency.