Reducing Subjectivity in the Likelihood

10.6339/JDS.2006.04(3).265

S. James Press

Mixture likelihood ； model averaging ； subjectivity

Journal of Data Science

4卷3期（2006 / 07 / 01）

307 - 321

英文

Some scientists prefer to exercise substantial judgment in formulating a likelihood function for their data. Others prefer to try to get the data to tell them which likelihood is most appropriate. We suggest here that one way to reduce the judgment component of the likelihood function is to adopt a mixture of potential likelihoods and let the data determine the weights on each likelihood. We distinguish several different types of subjectivity in the likelihood function and show with examples how these subjective elements may be given more equitable treatment.

1. 邱建晴(2016)。以卷積神經網路分析部落格社群網站垃圾文章。國立臺灣大學工程科學及海洋工程學系學位論文。2016。1-68。 
2. 陳而設(2016)。以索引值導向為基礎具高效率的新網格群集演算法。屏東科技大學資訊管理系所學位論文。2016。1-78。
3. 宋政(2016)。探討融入自我調整學習鷹架對九年級學生科學本質觀點之影響。交通大學教育研究所學位論文。2016。1-82。
4. 蔡春梅(2017)。醫美意象、知覺價值、顧客滿意度與購後行為意圖關係之研究-以南部某醫學美容集團為例。義守大學醫務管理學系學位論文。2017。1-115。