Algorithmic compression of empirical data: reply to Twardy, Gardner, and Dowe

被引:0
|
作者
McAllister, JW [1 ]
机构
[1] Leiden Univ, Fac Philosophy, NL-2300 RA Leiden, Netherlands
来源
STUDIES IN HISTORY AND PHILOSOPHY OF SCIENCE | 2005年 / 36A卷 / 02期
关键词
algorithmic compression; algorithmic randomness; empirical data; Huffman compression; Minimum Message Length technique;
D O I
10.1016/j.shpsa.2005.04.005
中图分类号
N09 [自然科学史]; B [哲学、宗教];
学科分类号
01 ; 0101 ; 010108 ; 060207 ; 060305 ; 0712 ;
摘要
This discussion note responds to objections by Twardy, Gardner, and Dowe to my earlier claim that empirical data sets are algorithmically incompressible. Twardy, Gardner, and Dowe hold that many empirical data sets are compressible by Minimum Message Length technique and offer this as evidence that these data sets are algorithmically compressible. I reply that the compression achieved by Minimum Message Length technique is different from algorithmic compression. I conclude that Twardy, Gardner, and Dowe fail to establish that empirical data sets are algorithmically compressible. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:403 / 410
页数:8
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