Representation of Knowledge for Chess Endgames Towards a Self-Improving System. - Max A. Bramer (1977)

Advances in computer chess. - Max Bramer (SIGART Newsl., 1978)

Testing Correctness of Strategies in Game-Playing Programs. - Max A. Bramer (IJCAI, 1979)

Correct and Optimal Strategies in Game Playing Programs. - Max A. Bramer (Comput. J., 1980)

Game-playing programs: theory and practice. - Max A. Bramer (SIGART Newsl., 1982)

A Rational Reconstruction of the MYCIN Consultation System. - Jadzia Cendrowska; Max A. Bramer (Int. J. Man Mach. Stud., 1984)

KPK Endgame Databases: A Response from the Source. - Max Bramer (J. Int. Comput. Games Assoc., 1986)

An Expert System for Solving Retrograde-Analysis Chess Problems. - B. E. P. Alden; Max A. Bramer (Int. J. Man Mach. Stud., 1988)

GAUSS: A Generalised Approach to Updating Scanner Strategies. - Elisabeth Bacon; Sati McKenzie; Mike Smith; John Bingham; Max Bramer (AIME, 1989)

Case-Based Reasoning: A Technique for "Decision Support Systems" in Residential Valuation and the Construction of Residential Housing. - Ilesh Dattani; Max Bramer (UK Workshop on Case-Based Reasoning, 1995)

Techniques for Dealing with Missing Values in Classification. - Wei Zhong Liu; Allan P. White; Simon G. Thompson; Max A. Bramer (IDA, 1997)

Concept dispersion, feature interaction and their effect on particular sources of bias in machine learning. - Kamal Nazar; Max A. Bramer (Knowl. Based Syst., 1998)

Es98. - Max Bramer (Knowl. Based Syst., 1999)

Using J-Pruning to Reduce Overfitting of Classification Rules in Noisy Domains. - Max Bramer (DEXA, 2002)

Pre-pruning Classification Trees to Reduce Overfitting in Noisy Domains. - Max Bramer (IDEAL, 2002)

An Information-Theoretic Approach to the Pre-pruning of Classification Rules. - Max Bramer (IIP, 2002)

Editorial. - Max Bramer (Knowl. Based Syst., 2002)

Using J-pruning to reduce overfitting in classification trees. - Max Bramer (Knowl. Based Syst., 2002)

Knowledge Web: a public domain expert system delivery environment. - Max Bramer (SMC, 2003)

Intelligent data analysis for conservation: experiments with rhino horn fingerprint identification. - Rajan Amin; Max Bramer; Richard Emslie (Knowl. Based Syst., 2003)

Impact on Performance of Hypertext Classification of Selective Rich HTML Capture. - Houda Benbrahim; Max Bramer (AIAI, 2004)

Neighbourhood Exploitation in Hypertext Categorization. - Houda Benbrahim; Max Bramer (SGAI Conf., 2004)

An empirical study for hypertext categorization. - Houda Benbrahim; Max Bramer (SMC (6), 2004)

Logic Programming with Prolog - Max Bramer (Springer, 2005)

Inducer: a public domain workbench for data mining. - Max Bramer (Int. J. Syst. Sci., 2005)

An Expert System Delivery Environment for the World Wide Web. - Max Bramer (AIAI, 2006)

Review of Current Crime Prediction Techniques. - Vikas Grover; Richard Adderley; Max Bramer (SGAI Conf. (Applications), 2006)

Exploring Web Search Results Clustering. - Xiaoxia Wang; Max Bramer (SGAI Conf., 2006)

Principles of Data Mining - Max Bramer (Springer, 2007)

Towards a Computationally Efficient Approach to Modular Classification Rule Induction. - Frederic T. Stahl; Max Bramer (SGAI Conf., 2007)

A Fuzzy Semi-Supervised Support Vector Machines Approach to Hypertext Categorization. - Houda Benbrahim; Max Bramer (IFIP AI, 2008)

P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction. - Frederic T. Stahl; Max A. Bramer; Mo Adda (IFIP AI, 2008)

Parallel Induction of Modular Classification Rules. - Frederic T. Stahl; Max Bramer; Mo Adda (SGAI Conf., 2008)

PMCRI: A Parallel Modular Classification Rule Induction Framework. - Frederic T. Stahl; Max A. Bramer; Mo Adda (MLDM, 2009)

Parallel Rule Induction with Information Theoretic Pre-Pruning. - Frederic T. Stahl; Max Bramer; Mo Adda (SGAI Conf., 2009)

Special Issue on Emerging Artificial Intelligence Applications and Innovations: Papers from AIAI 2006. - Ilias Maglogiannis; Kostas Karpouzis; Max Bramer (Appl. Intell., 2009)

Guest Editorial. - Max Bramer (Knowl. Based Syst., 2009)

Text and Hypertext Categorization. - Houda Benbrahim; Max Bramer (Artificial Intelligence: An International Perspective, 2009)

Pocket Data Mining: Towards Collaborative Data Mining in Mobile Computing Environments. - Frederic T. Stahl; Mohamed Medhat Gaber; Max Bramer; Philip S. Yu (ICTAI (2), 2010)

J-PMCRI: A Methodology for Inducing Pre-pruned Modular Classification Rules. - Frederic T. Stahl; Max Bramer; Mo Adda (IFIP AI, 2010)

Induction of Modular Classification Rules: Using Jmax-pruning. - Frederic T. Stahl; Max Bramer (SGAI Conf., 2010)

Distributed hoeffding trees for pocket data mining. - Frederic T. Stahl; Mohamed Medhat Gaber; Max Bramer; Philip S. Yu (HPCS, 2011)

Distributed Classification for Pocket Data Mining. - Frederic T. Stahl; Mohamed Medhat Gaber; Han Liu 002; Max Bramer; Philip S. Yu (ISMIS, 2011)

Random Prism: An Alternative to Random Forests. - Frederic T. Stahl; Max Bramer (SGAI Conf., 2011)

Parallel Random Prism: A Computationally Efficient Ensemble Learner for Classification. - Frederic T. Stahl; David May 004; Max Bramer (SGAI Conf., 2012)

Special Issue on Innovative techniques and applications of artificial intelligence. - Max Bramer (Knowl. Based Syst., 2012)

Jmax-pruning: A facility for the information theoretic pruning of modular classification rules. - Frederic T. Stahl; Max Bramer (Knowl. Based Syst., 2012)

Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks. - Frederic T. Stahl; Max Bramer (Knowl. Based Syst., 2012)

Homogeneous and Heterogeneous Distributed Classification for Pocket Data Mining. - Frederic T. Stahl; Mohamed Medhat Gaber; Paul Aldridge; David May 004; Han Liu 002; Max Bramer; Philip S. Yu (Trans. Large Scale Data Knowl. Centered Syst., 2012)

Principles of Data Mining, Second Edition. - Max A. Bramer (Springer, 2013)

Logic Programming with Prolog. - Max Bramer (Springer, 2013)

Scaling up classification rule induction through parallel processing. - Frederic T. Stahl; Max Bramer (Knowl. Eng. Rev., 2013)

Random Prism: a noise-tolerant alternative to Random Forests. - Frederic T. Stahl; Max Bramer (Expert Syst. J. Knowl. Eng., 2014)

Web Programming with PHP and MySQL - A Practical Guide - Max Bramer (Springer, 2015)

A Scalable Expressive Ensemble Learning Using Random Prism: A MapReduce Approach. - Frederic T. Stahl; David May 004; Hugo Mills; Max Bramer; Mohamed Medhat Gaber (Trans. Large Scale Data Knowl. Centered Syst., 2015)

Towards Expressive Modular Rule Induction for Numerical Attributes. - Manal Almutairi; Frederic T. Stahl; Mathew Jennings; Thien Le; Max Bramer (SGAI Conf., 2016)

Principles of Data Mining, Third Edition - Max Bramer (Springer, 2016)

Improving Modular Classification Rule Induction with G-Prism Using Dynamic Rule Term Boundaries. - Manal Almutairi; Frederic T. Stahl; Max Bramer (SGAI Conf., 2017)

A Rule-Based Classifier with Accurate and Fast Rule Term Induction for Continuous Attributes. - Manal Almutairi; Frederic T. Stahl; Max Bramer (ICMLA, 2018)

Principles of Data Mining, 4th Edition - Max Bramer (Springer, 2020)

ReG-Rules: An Explainable Rule-Based Ensemble Learner for Classification. - Manal Almutairi; Frederic T. Stahl; Max Bramer (IEEE Access, 2021)

CRC: Consolidated Rules Construction for Expressive Ensemble Classification. - Manal Almutairi; Frederic T. Stahl; Max Bramer (SGAI Conf., 2022)