tailieunhanh - Microsoft Data Mining integrated business intelligence for e commerc and knowledge phần 3

Phương pháp tiếp cận giảm rủi ro phù hợp với sự phát hiện của khách hàng người nghèo chống lại các ứng dụng đặc điểm rủi ro cho vay. Đề xuất này tháng đó quản lý rủi ro Một số thói quen không CẦN THIẾT Một số khách hàng với lợi nhuận tối đa hóa-một động thái. Đề xuất này cũng yêu cầu xử lý đặc biệt tháng nào khách hàng. | 48 Modeling Some data-driven approaches will produce adequate often superior predictive models even in the absence of a theoretical orientation. In this case you might be tempted to employ the maxim If it ain t broke don t fix it. In fact the best predictive models even if substantially data driven benefit greatly from a theoretical understanding. The best prediction emerges from a sound thorough and well-developed theoretical foundation knowledge is still the best ingredient to good prediction. The best predictive models available anywhere are probably weather prediction models although few of US care to believe this or would even admit it . This level of prediction would not be possible without a rich and well-developed science of meteorology and the associated level of understanding of the various factors and interrelationships that characterize variations in weather patterns. The prediction is also good because there is a lot of meterological modeling going on and there is an abundance of empirical data to validate the operation of the models and their outcomes. This is evidence of the value of the interative nature of good modeling regimes and of good science in general . Cluster analysis Cluster analysis can perhaps be best described with reference to the work completed by astronomers to understand the relationship between luminosity and temperatures in stars. As shown in the Hertzsprung-Russell diagram Figure stars can seem to cluster according to their shared similarities in temperature shown on the horizontal scale and luminosity shown on the vertical scale . As can be readily seen from this diagram stars tend to cluster into one of three groups white dwarfs main sequence and giants supergiants. If all our work in cluster analysis involved exploring the relationships between various observations records of analysis and two dimensions of analysis as shown here on the horizontal and vertical axes then we would be able to conduct a cluster .