Abstract
It is one thing to have an awareness of a subject but it is another to be an active and able worker in it. This chapter describes experiences, pitfalls, hints and tricks that may help the reader to get started at putting MML into practice. “Probability theory is nothing but common sense reduced to calculation” (Laplace) but data analysis software is numerical software and the results of computations need to be checked with scepticism, common sense and cunning.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
L. Allison, Models for machine learning and data mining in functional programming. J. Funct. Program. 15(1), 15–32 (2005). https://doi.org/10.1017/S0956796804005301
A.J. Bleasby, J.C. Wootton, Constructing validated, non-redundant composite protein sequence databases. Protein Eng. 3(3), 153–159 (1990). https://doi.org/10.1093/protein/3.3.153
G.E.P. Box, Robustness in the strategy of scientific model building. Robustness Stat. 1, 201–236 (1979). https://doi.org/10.1016/B978-0-12-438150-6.50018-2. Includes, “All models are wrong but some are useful”
S. Fienberg, When did Bayesian inference become “Bayesian”? Bayesian Anal. 1(1), 1–40 (2006). https://projecteuclid.org/download/pdf_1/euclid.ba/1340371071
J. Gosling, B. Joy, G. Steele, G. Bracha, A. Buckley, The Java Language Specification, Java SE 8 (Addison Wesley, Reading, MA, 2014). ISBN 978-0133900699
A.S. Konagurthu, L. Allison, D. Abramson, P.J. Stuckey, A.M. Lesk, How precise are reported protein coordinate data? Acta Crystallogr. D70(3), 904–906 (2014). https://doi.org/10.1107/S1399004713031787
S. Kullback, R.A. Leibler, On information and sufficiency. Ann. Math. Stat. 22(1), 79–86 (1951). https://doi.org/10.1214/aoms/1177729694
M. Nelson, Arithmetic coding + statistical modeling = data compression. Dr Dobbs J. (1991). http://marknelson.us/1991/02/01/arithmetic-coding-statistical-modeling-data-compression/
R.C. Pasco, Source coding algorithms for fast data compression. PhD thesis, Stanford University CA, 1976
S. Peyton Jones et al., Haskell 98 Language and Libraries, the Revised Report (Cambridge University Press, Cambridge, 2003). ISBN 978-0521826143
J. Rissanen, Generalized kraft inequality and arithmetic coding. IBM J. Res. Dev. 20(3), 198–203 (1976). https://doi.org/10.1147/rd.203.0198
P.H. Sellers, On the theory and computation of evolutionary distances. SIAM J. Appl. Math. 26(4), 787–793 (1974). https://doi.org/10.1137/0126070
B. Stroustrup, The C++ Programming Language: Special Edition (Addison Wesley, Reading, MA, 2000). ISBN 978-0201700732
C.S. Wallace, How to do inductive inference using information theory. Seminar, Department of Computer Science, Monash University, 1993. http://www.allisons.org/ll/Images/People/Wallace/1993-08-10/
C.S. Wallace, A brief history of MML. Seminar, Faculty of Information Technology, Monash University, 2003. http://www.allisons.org/ll/MML/20031120e/
C.S. Wallace, P.R. Freeman, Estimation and inference by compact coding. J. R. Stat. Soc. Ser. B Methodol. 240–265 (1987). http://www.jstor.org/stable/2985992
C.S. Wallace, J.D. Patrick, Coding decision trees. Mach. Learn. 11(1), 7–22 (1993). https://doi.org/10.1023/A:1022646101185
C.N. Yee, L. Allison, Reconstruction of strings past. J. Bioinformatics 9(1), 1–7 (1993). https://doi.org/10.1093/bioinformatics/9.1.1
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Allison, L. (2018). Bits and Pieces. In: Coding Ockham's Razor. Springer, Cham. https://doi.org/10.1007/978-3-319-76433-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-76433-7_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-76432-0
Online ISBN: 978-3-319-76433-7
eBook Packages: Computer ScienceComputer Science (R0)