Term Weighting Vs. Logistic Regression Performance on E-Commerce Data

cumulative logistic regression vs ordinary logistic regression

The common practice of collapsing inherently continuous or ordinal variables into two categories causes information loss that may potentially weaken power to detect effects of explanatory variables and result in Type II errors in statistical inference. The purpose of this investigation was to illustrate, using a substantive example, the potential increase in power gained from an ordinal instead...

Electronic Commerce Data Mining using Rough Set and Logistic Regression

Electronic commerce (E-commerce) has gradually been the mainstream of business. There may be some unpredictable but frequent problems such as delay in shipment, shipping errors caused by E-commerce participants’ low efficiency. There problems will have negative impact on the business of participants eventually. Correct evaluation of the efficiency of E-commerce is an important way to improve op...

Performance of Logistic Regression in Tuberculosis Data

This paper examined logistic regression for describing the relationship between an indications of suffering from complications pulmonary tuberculosis and its associated risk factors (predictors). Logistic regression was used as a tool to see the performance on tuberculosis data. The data used for this paper was collected from the Records Department of Federal Medical Centre, Ido Ekiti, Ekiti St...

Term-driven E-Commerce

Neural Networks vs Logistic Regression: a Comparative Study on a Large Data Set

Neural networks and logistic regression have been among the most widely used AI techniques in applications of pattern clussiftiution. MLK~ has been discrlssed about if there is any signzficunt d&erence in between them but much less has been actually done with real-world applications data (large scale) to help settle this mutter, with a few exceptions. This paper presents a performance compariso...