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Description Data Mining Techniques For Marketing_4

Tham khảo tài liệu 'description data mining techniques for marketing_4', khoa học xã hội, kinh tế chính trị phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 244 Chapter 7 determine how to interpret results. Neural Networks for Time Series In many business problems the data naturally falls into a time series. Examples of such series are the closing price of IBM stock the daily value of the Swiss franc to U.S. dollar exchange rate or a forecast of the number of customers who will be active on any given date in the future. For financial time series someone who is able to predict the next value or even whether the series is heading up Artificial Neural Networks 245 or down has a tremendous advantage over other investors. Although predominant in the financial industry time series appear in other areas such as forecasting and process control. Financial time series though are the most studied since a small advantage in predictive power translates into big profits. Neural networks are easily adapted for time-series analysis as shown in Figure 7.12. The network is trained on the time-series data starting at the oldest point in the data. The training then moves to the second oldest point and the oldest point goes to the next set of units in the input layer and so on. The network trains like a feed-forward back propagation network trying to predict the next value in the series at each step. Figure 7.12 A time-delay neural network remembers the previous few training examples and uses them as input into the network. The network then works like a feed-forward back propagation network. 246 Chapter 7 Notice that the time-series network is not limited to data from just a single time series. It can take multiple inputs. For instance to predict the value of the Swiss franc to U.S. dollar exchange rate other time-series information might be included such as the volume of the previous day s transactions the U.S. dollar to Japanese yen exchange rate the closing value of the stock exchange and the day of the week. In addition non-time-series data such as the reported inflation rate in the countries over the period of time under investigation