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Research Output for Zijian Zheng

Note: The 2012, 2013, 2014 publications have not been audited.

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Publications

2000 School of Information Technology

Zheng, Z. (2000) Constructing conjunctive attributes using production rules, Journal of Research and Practice in Information Technology, vol. 0, no. 0, pp. 13-38, Australian Computer Society Inc., The Netherlands [C1]
ERA journal ID: Not matching ERA journal list
no DRO entry yet for this publication

Zheng, Z. (2000) Constructing X-of-N Attributes for Decision Tree Learning, Machine Learning, vol. 0, no. 0, pp. 35-75, Kluwer Academic Publishers, The Netherlands [C1]
ERA journal ID: 18066 – Scopus EID: Not tagged
no DRO entry yet for this publication

Zheng, Z. and Webb, G. (2000) Lazy learning of Bayesian rules, Machine Learning, vol. 0, no. 0, pp. 53-84, Kluwer Academic Publishers, Netherlands [C1]
ERA journal ID: 18066 – Scopus EID: Not tagged
no DRO entry yet for this publication

Ting, K., Zheng, Z. and Webb, G. (2000) Learning lazy rules to improve the performance of classifiers, in Max Bramer, Ann Macintosh and Frans Coenen (eds), Proceedings of ES99: The 19th SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, pp. 122-131, Springer-Verlag, London [E1]
no DRO entry yet for this publication

1999 School of Information Technology

Webb, Geoff., Wells, Jason. and Zheng, Zijian (1999) An experimental evaluation of integrating machine learning with knowledge acquisition , Machine Learning, vol. 0, no. 0, pp. 5-23, Kluwer Academic Press, Boston, MA, USA [C1]
ERA journal ID: 18066 – Scopus EID: Not tagged
no DRO entry yet for this publication

Ting, K. and Zheng, Z. (1999) Improving the performance of boosting for naive Bayesian classification, in N. Zhong & L. Zhou (eds), 3rd Pacific Asia Conference on knowledge discovery and data mining, pp. 296-305, Springer-Verlag, Berlin [E1]
no DRO entry yet for this publication

Zheng, Z. and Webb, G. (1999) Stochastic attribute selection committees with multiple boosting: learning more accurate and more stable classifier committees, in Ning Zhong and Lizhu Zhou (eds), 'Methodologies for knowledge discovery and data mining' 3rd Pacific-Asia Conference, pp. 123-132, Springer, Berlin [E1]
no DRO entry yet for this publication

Zheng, Z. and Low, B.* (1999) Classifying Unseen Cases with Many Missing Values, in Ning Zhong and Lizhu Zhou (eds), "Methodologies for knowledge discovery and data mining', pp. 370-374, Springer, Berlin [E1]
no DRO entry yet for this publication

1999 External

Zheng, Z.*, Webb, G. and Ting, K. (1999) Lazy Bayesian Rules: A lazy semi-naive Bayesian learning technique competitive to boosting decision trees, in Ivan Bratko and Saso Dzeroski (eds), Machine learning, proceedings of the 16th international conference, pp. 493-502, Morgan Kaufmann, California [E1]
no DRO entry yet for this publication

1998 School of Information Technology

Zheng, Z. (1998) A Comparison of Constructing Different Types of New Feature for Decision Tree Learning, "Feature Extraction, Construction and Selection: a Data Mining Perspective", pp. 239-255, Kluwer Academic Publishers, "Norwell, Massachusetts, USA" [B1]
no DRO entry yet for this publication

Zheng, Z. (1998) Constructing Conjunctions Using Systematic Search on Decision Trees, Knowledge-Based Systems, vol. 0, no. 0, pp. 421-430, Elsevier Science B.V., "Amsterdam, Netherlands" [C1]
ERA journal ID: Not matching ERA journal list
no DRO entry yet for this publication

Ting, K. and Zheng, Z. (1998) Boosting Cost-Sensitive Trees, First International Conference on Discovery Science, pp. 244-255, Springer-Verlag, "Berlin, Germany" [E1]
no DRO entry yet for this publication

Ting, K.* and Zheng, Z. (1998) Boosting Trees for Cost-Sensitive Classifications, 10th European Conference on Machine Learning, pp. 190-195, Springer-Verlag, Berlin [E1]
no DRO entry yet for this publication

Zheng, Z., Webb, G. and Ting, K. (1998) Integrating Boosting and Stochastic Attribute Selection Committees for Further Improving the Performance of Decision Tree Learning, 10th International Conference on Tools With Artificial Intelligence TAI '98, pp. 216-223, IEEE Computer Society, "Los Alamitos, USA" [E1]
no DRO entry yet for this publication

Zheng, Z. and Webb, G. (1998) Multiple Boosting: A Combination of Boosting and Bagging, The International Conference on Parallel and Distributed Processing Techniques and Applications, pp. 1133-1140, CSREA, USA [E1]
no DRO entry yet for this publication

Zheng, Z. (1998) Scaling Up the Rule Generation of C4.5, Research and Development in Knowledge Discovery and Data Mining, pp. 348-359, Springer-Verlag, "Berlin, Germany" [E1]
no DRO entry yet for this publication

Zheng, Z. (1998) Naive Bayesian Classifier Committees, 10th European Conference on Machine Learning, pp. 196-207, Springer-Verlag, "Berlin, Germany" [E1]
no DRO entry yet for this publication

Zheng, Z. (1998) Generating Classifier Committees by Stochastically Selecting Both Attributes and Training Examples, 5th Pacific Rim International Conference on Artificial Intelligence, pp. 12-23, Springer-Verlag, "Berlin, Germany" [E1]
no DRO entry yet for this publication

Zheng, Z. and Webb, G. (1998) Stochastic Attribute Selection Committees, 11th Australian Joint Conference on Artificial Intelligence, pp. 321-332, Springer-Verlag, "Berlin, Germany" [E1]
no DRO entry yet for this publication

1997 School of Information Technology

Chiu, B., Webb, G. and Zheng, Z. (1997) Using Decision Trees for Agent Modelling: A Study on Resolving Conflicting Predictions., Proceedings of the Tenth Australian Joint Conference on Artificial Intelligence (AI'97), pp. 349-358, Springer-Verlag, Berlin [E1]
no DRO entry yet for this publication

Zheng, Z. (1997) Constructing Conjunctions using Systematic Search on Decision Trees, Proceedings of the First Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 88-101, World Scientific, Singapore [E1]
no DRO entry yet for this publication

1996 School of Information Technology

Zheng, Z. (1996) Effects of Different Types of New Attribute on Constructive Induction, Proceedings of Eighth IEEE International Conference on Tools with Artificial Intelligence, pp. 254-257, IEE Computer Society Press, California, USA [E1]
no DRO entry yet for this publication

Grants and Consultancies

All years

Research Income - National Competitive Grants

Webb, G, Pazzani, M* and Zheng, Z*. Learning efficient accurate Bayesian classifiers from data, Australian Research Council Large Grant [T]

  • 2000: $56,971

Higher Degree by Research Completions supervised by Zijian Zheng

No completions found or audited.

Legend:
* Not a member of Deakin University at time of output.

DRO to publications collection last synchronised: Wednesday 20th August 2014 10:04pm

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23rd July 2011