Types and classes of machine learning and data mining

Authors:
Lloyd Allison
Affiliations:
School of Computer Science and Software Engineering, Monash University, Clayton, Victoria, Australia
Venue:
ACSC '03 Proceedings of the 26th Australasian computer science conference - Volume 16
Year:
2003

Citing 7
Cited 1

Report on the programming language Haskell: a non-strict, purely functional language version 1.2

ACM SIGPLAN Notices - Haskell special issue
C4.5: programs for machine learning

C4.5: programs for machine learning
Data mining: practical machine learning tools and techniques with Java implementations

Data mining: practical machine learning tools and techniques with Java implementations
Unsupervised Learning of Finite Mixture Models

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Programming Language Semantics

A Theory of Programming Language Semantics
Fundamental Concepts in Programming Languages

Higher-Order and Symbolic Computation
The Calculi of Lambda Conversion. (AM-6) (Annals of Mathematics Studies)

The Calculi of Lambda Conversion. (AM-6) (Annals of Mathematics Studies)

A programming paradigm for machine learning, with a case study of Bayesian networks

ACSC '06 Proceedings of the 29th Australasian Computer Science Conference - Volume 48

Quantified Score

Hi-index	0.00

Visualization

Abstract

The notion of a statistical model, as inferred and used in statistics, machine learning and data mining, is examined from a semantic point of view. Data types and type-classes for models are developed that allow models to be manipulated in a type-safe yet flexible way. The programming language Haskell-98, with its system of polymorphic types and type-classes, is used as the meta-language for this exercise so one of the by-products is a running program.