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With the rapid development of real estate, the risk of investment is also increasing rapidly. So the risk of predicting and controlling the real estate investment has become the key to the success or failure of the project. In this paper, a support vector machine (SVM) modeling approach for real estate investment risk prediction is proposed at first, which is made use of its merits of structural risk minimization principle, the small study sample and non-linear to analyze the risk factors during investment every stage in real estate projects, then a model based on support vector machines in real estate investment risk is built up, at last, an example is given to prove that this model is effective and practical. All these are used of providing useful help of the future of real estate investment risk control and management.
Date of Conference: 23-25 Jan. 2009