کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10368165 | 874193 | 2005 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An experimental investigation of the impact of aggregation on the performance of data mining with logistic regression
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سیستم های اطلاعاتی
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چکیده انگلیسی
We studied the impact of data aggregation on the performance of logistic regression on predicting the direction of the Dow Jones industrial average (DJIA) stock market index. Data aggregation is a common operation in business, science, engineering, medicine, etc.; it is performed for purposes such as statistical, financial, and sales and marketing analysis - particularly within the context of a data warehouse. We showed experimentally that, for this example, as long as aggregation does not shrink the sample size unduly, it does not significantly impair the performance of the logistic regression model for predicting the direction of the DJIA stock market index. We also observed that aggregation-based models are simpler (less over-parameterized) than detail-based models. We used the receiver operating characteristic (ROC) analysis to evaluate the robustness of such predictive models. Specifically, we used the area under the ROC curve as a summary measure of the overall performance of a given model.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information & Management - Volume 42, Issue 5, July 2005, Pages 695-707
Journal: Information & Management - Volume 42, Issue 5, July 2005, Pages 695-707
نویسندگان
Adam Fadlalla,