College graduates employment prediction based on Principal Component Analysis and the combined adaptive boosting and the back propagation neural network algorithm

In order to improve the prediction accuracy of the back propagation (BP) neural network model, a prediction model is presented based on the combined adaptive boosting (AdaBoost) and the back propagation neural network algorithm. The efficiency of the proposed prediction model is proved by predicting the college graduates employment. The computer simulations have shown that this model is effective and suitable. It has higher prediction accuracy and is applicable to practice.