Technical Note: Naive Bayes for Regression
作者:Eibe Frank, Leonard Trigg, Geoffrey Holmes, Ian H. Witten
摘要
Despite its simplicity, the naive Bayes learning scheme performs well on most classification tasks, and is often significantly more accurate than more sophisticated methods. Although the probability estimates that it produces can be inaccurate, it often assigns maximum probability to the correct class. This suggests that its good performance might be restricted to situations where the output is categorical. It is therefore interesting to see how it performs in domains where the predicted value is numeric, because in this case, predictions are more sensitive to inaccurate probability estimates.
论文关键词:naive Bayes, regression, model trees, linear regression, locally weighted regression
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论文官网地址:https://doi.org/10.1023/A:1007670802811