Reducing large datasets to improve the identification of estimated policy rules

Author(s):  
Omer Bayar
Keyword(s):  
2017 ◽  
Vol 25 (2) ◽  
pp. 927-960
Author(s):  
Jarod Jacobs

In this article, I discuss three statistical tools that have proven pivotal in linguistic research, particularly those studies that seek to evaluate large datasets. These tools are the Gaussian Curve, significance tests, and hierarchical clustering. I present a brief description of these tools and their general uses. Then, I apply them to an analysis of the variations between the “biblical” DSS and our other witnesses, focusing upon variations involving particles. Finally, I engage the recent debate surrounding the diachronic study of Biblical Hebrew. This article serves a dual function. First, it presents statistical tools that are useful for many linguistic studies. Second, it develops an analysis of the he-locale, as it is used in the “biblical” Dead Sea Scrolls, Masoretic Text, and Samaritan Pentateuch. Through that analysis, this article highlights the value of inferential statistical tools as we attempt to better understand the Hebrew of our ancient witnesses.


2018 ◽  
Author(s):  
Andrew Dalke ◽  
Jerome Hert ◽  
Christian Kramer

We present mmpdb, an open source Matched Molecular Pair (MMP) platform to create, compile, store, retrieve, and use MMP rules. mmpdb is suitable for the large datasets typically found in pharmaceutical and agrochemical companies and provides new algorithms for fragment canonicalization and stereochemistry handling. The platform is written in Python and based on the RDKit toolkit. mmpdb is freely available.


2012 ◽  
Vol 38 (11) ◽  
pp. 1831
Author(s):  
Wen-Jun HU ◽  
Shi-Tong WANG ◽  
Juan WANG ◽  
Wen-Hao YING

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