Support Vector Machine For Regression Analysis And Application In Drug Sales Forecasts

With the wide application of database system in the modern enterprises, the enterprise informationization process is in the stage of continuous improvement. However, the "knowledge" contained in a mass of data accumulated by the enterprises, which is beneficial to enterprise decision, has not been used effectively. Data Mining is just brought to resolve this contradiction. It is currently applied to many fields covering finance, electric power, telecommunications, transportation and many others. As an important part of data mining, predication has caused the concern of the enterprises the researchers.In modern society, a relatively accurate predication plays an important role; it helps companies and units make the right decisions and thus promote their development. It is particularly important to the marketing industry. An accurate predication is very important to Medicament sales, for it enabling enterprises to reasonable arrangements for business invoicing, saving costs, maximizing the benefits. Although the prediction is very important, but high-quality prediction is not easy. How to select appropriate data mining techniques on the basis of a prediction quality assurance.As a new technology, Support Vector Machines in data mining based on structural risk optimization theory has solved the "over learning" phenomenon in other technology, used kernel function to avoid the "curse of dimension", and shown good predication Performance in many fields. In this paper, Support Vector Machines through a systematic exposition of the theory, for the pharmaceutical sales industry, introduces the use of Support Vector Machine regression algorithm to the problem of Medicament sales to establish prediction model of the steps. Use of relevant software simulation and implementation of forecasting models, and stressed that the model design process sales data extraction, preprocessing methods, model validation and other issues. Want to solve their own problems of Medicament sales companies to provide some reference. In this paper, through a systematic exposition of Support Vector Machines correlation theory , for the Medicament sales, introduces the steps of the construction of predication model by using Support Vector Machine regression algorithm. Used relevant software for simulation study and implementation of predication models, and stressed the methods of sales data extraction and preprocessing, model validation and other issues in model design process, Want to provide some references for solving the problems of Medicament sales.