C. Drummond

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Composing Functions to Speed up Reinforcement Learning in a Changing World

Chris Drummond, C. Drummond, 1998, ECML.

A symbol's role in learning low-level control functions

R. Holte, C. Drummond, 1999 .

Replicability is not Reproducibility:Nor is it Good Science

C. Drummond, 2009 .

Accelerating Reinforcement Learning by Composing Solutions of Automatically Identified Subtasks pdf

Chris Drummond, C. Drummond, 2011, J. Artif. Intell. Res..

Finding a Balance between Anarchy and Orthodoxy

C. Drummond, 2008 .

Learning to Live with False Alarms

Chris Drummond, Chris. Drummond, R. Holte, 2005 .

Making Evaluation Robust but Robust to What ?

C. Drummond, 2007 .

Robust but Robust to What ?

C. Drummond, 2007 .

Exploiting the Cost (In)sensitivity of Decision Tree Splitting Criteria

Robert C. Holte, Chris Drummond, R. Holte, 2000, ICML.

Reverse-Engineering Costs : How much will a Prognostic Algorithm save ?

Chris Drummond, Chunsheng Yang, C. Drummond, 2008 .

Machine Learning as an Experimental Science ( Revisited ) ∗

Chris. Drummond, C. Drummond, 2006 .

GT 2009-60148 IMPROVED COMPRESSOR MAPS USING APPROXIMATE SOLUTIONS TO THE

C. Drummond, 2009 .

Workshop summary: The fourth workshop on evaluation methods for machine learning

Nathalie Japkowicz, Chris Drummond, Sofus A. Macskassy, 2009, International Conference on Machine Learning.

Beyond the Boundaries of SMOTE - A Framework for Manifold-Based Synthetically Oversampling

Nathalie Japkowicz, Chris Drummond, Colin Bellinger, 2016, ECML/PKDD.

Reproducible research: a minority opinion

Chris Drummond, C. Drummond, 2018, J. Exp. Theor. Artif. Intell..

Severe Class Imbalance: Why Better Algorithms Aren't the Answer

Robert C. Holte, Chris Drummond, R. Holte, 2005, ECML.

C4.5, Class Imbalance, and Cost Sensitivity: Why Under-Sampling beats Over-Sampling

Robert C. Holte, Chris Drummond, R. Holte, 2003 .

Explicitly representing expected cost: an alternative to ROC representation

Robert C. Holte, Chris Drummond, R. Holte, 2000, KDD '00.

Discriminative vs. Generative Classifiers for Cost Sensitive Learning

Chris Drummond, C. Drummond, 2006, Canadian Conference on AI.

Learning Multi-dimensional Functions: Gas Turbine Engine Modeling

Chris Drummond, C. Drummond, 2007, PKDD.

INFERRING AND REVISING THEORIES WITH CONFIDENCE: ANALYZING BILINGUALISM IN THE 1901 CANADIAN CENSUS

Stan Matwin, Chris Drummond, Chad Gaffield, 2006, Appl. Artif. Intell..

Inferring and Revising Theories with Confidence: Analyzing the 1901 Canadian Census

Stan Matwin, Chris Drummond, Chad Gaffield, 2000 .

Manifold-based synthetic oversampling with manifold conformance estimation

Nathalie Japkowicz, Chris Drummond, Colin Bellinger, 2018, Machine Learning.

Inner Ensembles: Using Ensemble Methods Inside the Learning Algorithm

Stan Matwin, Nathalie Japkowicz, Chris Drummond, 2013, ECML/PKDD.

C 4 . 5 , Class Imbalance , and Cost Sensitivity : Why Under-Sampling beats OverSampling

Chris. Drummond, R. Holte, C. Drummond, 2003 .

Is the drive for reproducible science having a detrimental effect on what is published?

Chris Drummond, C. Drummond, 2019, Learn. Publ..

Cost curves: An improved method for visualizing classifier performance

Robert C. Holte, Chris Drummond, R. Holte, 2006, Machine Learning.

A Learning Agent that Assists the Browsing of Software Libraries

Dan Ionescu, Robert C. Holte, Chris Drummond, 2000, IEEE Trans. Software Eng..

Accelerating browsing by automatically inferring a user's search goal

Dan Ionescu, Robert C. Holte, Chris Drummond, 1993, Proceedings of 8th Knowledge-Based Software Engineering Conference.

Automatic goal extraction from user actions to accelerate the browsing of software libraries.

Chris Drummond, C. Drummond, 1993 .

Warning: statistical benchmarking is addictive. Kicking the habit in machine learning

Nathalie Japkowicz, Chris Drummond, C. Drummond, 2010, J. Exp. Theor. Artif. Intell..

Cost-sensitive classifier evaluation

Robert C. Holte, Chris Drummond, R. Holte, 2005, UBDM '05.

What ROC Curves Can't Do (and Cost Curves Can)

Robert C. Holte, Chris Drummond, R. Holte, 2004, ROCAI.

Discriminative vs. Generative Classifiers: An In-Depth Experimental Comparison using Cost Curves *

Chris Drummond, C. Drummond, 2005 .

Improving Bayesian Learning Using Public Knowledge

C. Drummond, N. Japkowicz, S. Matwin, 2010, Canadian Conference on AI.

Synthetic Oversampling for Advanced Radioactive Threat Detection

Nathalie Japkowicz, Chris Drummond, Colin Bellinger, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

A Learning Apprentice For Browsing

Robert C. Holte, Chris Drummond, R. Holte, 1994 .