Feature selection with RVM and its application to prediction modeling

被引：0

作者：

Li, Dingfang ^{[1
]}

Hu, Wenchao ^{[1
]}

机构：

[1] Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China

来源：

AI 2006: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2006年 / 4304卷

关键词：

RVM; feature selection; solubility; permeability; prediction;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We describe here a method named FSRVM-PLS for model construction using relevance vector machine (RVM). The most compelling feature of FSRVM-PLS is that it's not necessary to estimate parameters in the feature selection phase benefiting from a fully probabilistic framework. After evaluating the effectiveness of FSRVM on a synthetic data set, our method is applied successfully to the prediction of aqueous solubility and permeability.

引用

页码：1140 / +

页数：2

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