Method Researches Of Investment Estimate Based On SVM

There are a lot of problems of investment control in project for a long time. For example, it always happens that budgetary estimate is beyond basic estimate, budget is beyond budgetary estimate and final accounts is beyond budget. The investment control in the early period is made less focus on and even in the early period, there are many problems. It is important research to find a suit method to estimate the project cost quickly and exactly.Because empirical risk minimization and asymptotic theories is suitable to deal with situations where the amount of samples is tremendous and even infinite. However, in the project practice, finite and little amount of samples is usually present. So a novel promising machine learning technique specifically developed for analyzing little amount of samples, SVM (Support Vector Machine), will be more suitable in practical project application. It is given in the paper that feasibility and validity of SVM application in project practice and researches of investment control and investment estimate.