{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T16:57:47Z","timestamp":1790701067946,"version":"4.1.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2000,3,1]],"date-time":"2000-03-01T00:00:00Z","timestamp":951868800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2000,3,1]],"date-time":"2000-03-01T00:00:00Z","timestamp":951868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Machine Learning"],"published-print":{"date-parts":[[2000,3]]},"DOI":"10.1023\/a:1007631014630","type":"journal-article","created":{"date-parts":[[2002,12,22]],"date-time":"2002-12-22T05:54:50Z","timestamp":1040536490000},"page":"309-338","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":134,"title":["Multiple Comparisons in Induction Algorithms"],"prefix":"10.1007","volume":"38","author":[{"given":"David D.","family":"Jensen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul R.","family":"Cohen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","reference":[{"key":"253272_CR1","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1145\/76359.76371","volume":"36","author":"A. Blumer","year":"1989","unstructured":"Blumer, A., Ehrenfeucht, A., Haussler, D., & Warmuth, M. (1989). Learnability and the Vapnik-Chervonenkis dimension. Journal of the ACM, 36, 929\u2013965.","journal-title":"Journal of the ACM"},{"key":"253272_CR2","volume-title":"Classification and Regression Trees","author":"L. Breiman","year":"1984","unstructured":"Breiman, L., Friedman, J., Olshen, R., & Stone, C. (1984). Classification and Regression Trees. Belmont, CA: Wadsworth International."},{"key":"253272_CR3","first-page":"99","volume-title":"Training Issues in Incremental Learning: Papers from the 1993 Spring Symposium","author":"C. Brodley","year":"1993","unstructured":"Brodley, C. & Rissland, E. (1993). Measuring concept change. Training Issues in Incremental Learning: Papers from the 1993 Spring Symposium (pp. 99\u2013108). Menlo Park, CA: AAAI Press."},{"key":"253272_CR4","volume-title":"Empirical Methods for Artificial Intelligence","author":"P. R. Cohen","year":"1995","unstructured":"Cohen, P. R. (1995). Empirical Methods for Artificial Intelligence. Cambridge, MA: MIT Press."},{"key":"253272_CR5","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1145\/212094.212114","volume":"27","author":"T. Dietterich","year":"1995","unstructured":"Dietterich, T. (1995). Overfitting and under-computing in machine learning. ACM Computing Surveys, 27, 326\u2013327.","journal-title":"ACM Computing Surveys"},{"key":"253272_CR6","volume-title":"Randomization Tests","author":"E. Edgington","year":"1995","unstructured":"Edgington, E. (1995). Randomization Tests (3rd edition). New York, NY: Marcel Dekker.","edition":"3rd edition"},{"key":"253272_CR7","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1086\/268019","volume":"36","author":"H. Einhorn","year":"1972","unstructured":"Einhorn, H. (1972). Alchemy in the behavioral sciences. Public Opinion Quarterly, 36, 367\u2013378.","journal-title":"Public Opinion Quarterly"},{"key":"253272_CR8","first-page":"104","volume-title":"Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92)","author":"U. Fayyad","year":"1992","unstructured":"Fayyad, U. & Irani, K. (1992). The attribute selection problem in decision tree generation. Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92) (pp. 104\u2013110). Menlo Park, CA: AAAI Press."},{"key":"253272_CR9","volume-title":"Learning from Data: Artificial and Intelligence V","author":"A. Feelders","year":"1996","unstructured":"Feelders, A. & Verkooijen, W. (1996). On the statistical comparison of inductive learning methods. In D. Fisher & H.-J. Lenz (Eds.), Learning from Data: Artificial and Intelligence V. New York, NY: Springer Verlag."},{"key":"253272_CR10","first-page":"22","volume-title":"Proceedings of the Fifth International Conference on Machine Learning","author":"D. Fisher","year":"1988","unstructured":"Fisher, D. & Schlimmer, J. (1988). Concept simplification and prediction accuracy. Proceedings of the Fifth International Conference on Machine Learning (pp. 22\u201328). San Mateo, CA: Morgan Kaufmann."},{"key":"253272_CR11","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/B978-1-55860-036-2.50046-1","volume-title":"Proceedings of the Sixth International Workshop on Machine Learning","author":"B. Gaines","year":"1989","unstructured":"Gaines, B. (1989). An ounce of knowledge is worth a ton of data: Quantitative studies of the trade-off between expertise and data based on statistically well-founded empirical induction. Proceedings of the Sixth International Workshop on Machine Learning (pp. 156\u2013159). San Mateo, CA: Morgan Kaufmann."},{"key":"253272_CR12","first-page":"435","volume-title":"Proceedings of the Tenth European Conference on Artificial Intelligence","author":"O. Gascuel","year":"1992","unstructured":"Gascuel, O. & Caraux, G. (1992). Statistical significance in inductive learning. Proceedings of the Tenth European Conference on Artificial Intelligence (pp. 435\u2013439). Chichester: Wiley."},{"key":"253272_CR13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1162\/neco.1992.4.1.1","volume":"4","author":"S. Geman","year":"1992","unstructured":"Geman, S., Bienenstock, E., & Doursat, R. (1992). Neural networks and the bias\/variance dilemma. Neural Computation, 4, 1\u201358.","journal-title":"Neural Computation"},{"key":"253272_CR14","doi-asserted-by":"crossref","DOI":"10.1007\/978-94-009-3143-5","volume-title":"Multivariate Analysis of Variance and Repeated Measures: A Practical Approach for Behavioural Scientists","author":"D. Hand","year":"1987","unstructured":"Hand, D. & Taylor, C. (1987). Multivariate Analysis of Variance and Repeated Measures: A Practical Approach for Behavioural Scientists. London: Chapman and Hall."},{"key":"253272_CR15","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511897375","volume-title":"Topics in Applied Multivariate Analysis","author":"D. Hawkins","year":"1982","unstructured":"Hawkins, D. & Kass, G. (1982). Automatic interation detection. In D. Hawkins (Ed.), Topics in Applied Multivariate Analysis. Cambridge: Cambridge University Press."},{"key":"253272_CR16","first-page":"73","volume-title":"Proceedings of the Fifth International Conference on Machine Learning","author":"W. Iba","year":"1988","unstructured":"Iba, W., Wogulis, J., & Langley, P. (1988). Trading off simplicity and coverage in incremental concept learning. Proceedings of the Fifth International Conference on Machine Learning (pp. 73\u201379). San Mateo, CA: Morgan Kaufmann."},{"key":"253272_CR17","first-page":"148","volume-title":"Proceedings of the 1991 Knowledge Discovery in Databases Workshop","author":"D. Jensen","year":"1991","unstructured":"Jensen, D. (1991). Knowledge discovery through induction with randomization testing. Proceedings of the 1991 Knowledge Discovery in Databases Workshop (pp. 148\u2013159). Menlo Park, CA: AAAI."},{"key":"253272_CR18","volume-title":"Induction with Randomization Testing: Decision-Oriented Analysis of Large Data Sets","author":"D. Jensen","year":"1992","unstructured":"Jensen, D. (1992). Induction with Randomization Testing: Decision-Oriented Analysis of Large Data Sets. Doctoral dissertation. St. Louis, MO: Washington University."},{"key":"253272_CR19","first-page":"195","volume-title":"Proceedings of the Third International Conference on Knowledge Discovery and Data Mining","author":"D. Jensen","year":"1997","unstructured":"Jensen, D. & Schmill, M. (1997). Adjusting for multiple comparisons in decision tree pruning. Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (pp. 195\u2013198). Menlo Park, CA: AAAI Press."},{"key":"253272_CR20","doi-asserted-by":"crossref","first-page":"178","DOI":"10.2307\/2346565","volume":"24","author":"G. Kass","year":"1975","unstructured":"Kass, G. (1975). Significance testing in Automatic Interaction Detection (A.I.D.). Applied Statistics, 24, 178\u2013189.","journal-title":"Applied Statistics"},{"key":"253272_CR21","doi-asserted-by":"crossref","first-page":"119","DOI":"10.2307\/2986296","volume":"29","author":"G. Kass","year":"1980","unstructured":"Kass, G. (1980). An exploratory technique for investigating large quantities of categorical data. Applied Statistics, 29, 119\u2013127.","journal-title":"Applied Statistics"},{"key":"253272_CR22","first-page":"1137","volume-title":"IJCAI: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence","author":"R. Kohavi","year":"1995","unstructured":"Kohavi, R. (1995). A study of cross-validation and bootstrap for accuracy estimation and model selection. IJCAI: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (pp. 1137\u20131143). San Francisco, CA: Morgan Kaufmann."},{"key":"253272_CR23","first-page":"275","volume-title":"Proceedings of the Thirteenth International Conference on Machine Learning","author":"R. Kohavi","year":"1996","unstructured":"Kohavi, R. & Wolpert, D. (1996). Bias plus variance decomposition for zero-one loss functions. Proceedings of the Thirteenth International Conference on Machine Learning (pp. 275\u2013283). San Francisco, CA: Morgan Kaufmann."},{"key":"253272_CR24","first-page":"25","volume":"15","author":"W. Liu","year":"1994","unstructured":"Liu, W. & White, A. (1994). The importance of attribute selection measures in decision tree induction. Machine Learning, 15, 25\u201341.","journal-title":"Machine Learning"},{"key":"253272_CR25","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4613-8122-8","volume-title":"Simultaneous Statistical Inference","author":"R. Miller","year":"1981","unstructured":"Miller, R. (1981). Simultaneous Statistical Inference (2nd edition). New York, NY: Springer-Verlag.","edition":"2nd edition"},{"key":"253272_CR26","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1023\/A:1022604100933","volume":"4","author":"J. Mingers","year":"1989a","unstructured":"Mingers, J.(1989a).An empirical comparison of pruning methods for decision tree induction.Machine Learning,4,227\u2013243.","journal-title":"Machine Learning"},{"key":"253272_CR27","first-page":"319","volume":"3","author":"J. Mingers","year":"1989","unstructured":"Mingers, J.(1989b).Anempirical comparison of selection measures for decision-tree induction.Machine Learning,3, 319\u2013342.","journal-title":"Machine Learning"},{"key":"253272_CR28","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1086\/268066","volume":"37","author":"J. Morgan","year":"1973","unstructured":"Morgan, J. & Andrews, F. (1973).A comment on Einhorn's \u201cAlchemy in the behavioral sciences\u201d.Public Opinion Quarterly, 37,127\u2013129.","journal-title":"Public Opinion Quarterly"},{"key":"253272_CR29","first-page":"1025","volume-title":"IJCAI: Proceedings of Fourteenth International Joint Conference on Artificial Intelligence","author":"S. Murthy","year":"1995","unstructured":"Murthy, S. & Salzberg, S. (1995). Lookahead and pathology in decision tree induction. IJCAI: Proceedings of Fourteenth International Joint Conference on Artificial Intelligence (pp. 1025\u20131031). San Francisco, CA: Morgan Kaufmann."},{"key":"253272_CR30","volume-title":"Computer-Intensive Methods for Testing Hypotheses: An Introduction","author":"E. Noreen","year":"1989","unstructured":"Noreen, E. (1989). Computer-Intensive Methods for Testing Hypotheses: An Introduction. New York, NY: Wiley."},{"key":"253272_CR31","first-page":"254","volume-title":"Proceedings of the Fourteenth International Conference on Machine Learning","author":"T. Oates","year":"1997","unstructured":"Oates, T. & Jensen, D. (1997). The effects of training set size on decision tree complexity. Proceedings of the Fourteenth International Conference on Machine Learning (pp. 254\u2013262). San Francisco, CA: Morgan Kaufmann."},{"key":"253272_CR32","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1080\/03081077808960690","volume":"4","author":"J. Pearl","year":"1978","unstructured":"Pearl, J. (1978). On the connection between the complexity and credibility of inferred models. International Journal of General Systems, 4, 255\u2013264.","journal-title":"International Journal of General Systems"},{"key":"253272_CR33","first-page":"81","volume":"1","author":"J. R. Quinlan","year":"1986","unstructured":"Quinlan, J. R. (1986). Induction of decision trees. Machine Learning, 1, 81\u2013106.","journal-title":"Machine Learning"},{"key":"253272_CR34","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/S0020-7373(87)80053-6","volume":"27","author":"J. R. Quinlan","year":"1987","unstructured":"Quinlan, J. R. (1987). Simplifying decision trees. International Journal of Man-Machine Studies, 27, 221\u2013234.","journal-title":"International Journal of Man-Machine Studies"},{"key":"253272_CR35","volume-title":"Machine Intelligence","author":"J. R. Quinlan","year":"1988","unstructured":"Quinlan, J. R. (1988). Decision trees and multi-valued attributes. In J. Hayes, D. Michie & J. Richards (Eds.), Machine Intelligence (Vol. 11). Oxford, England: Clarendon Press."},{"key":"253272_CR36","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1613\/jair.279","volume":"4","author":"J. R. Quinlan","year":"1996","unstructured":"Quinlan, J. R. (1996). Improved use of continuous attributes in C4.5. Journal of Artificial Intelligence Research, 4, 77\u201390.","journal-title":"Journal of Artificial Intelligence Research"},{"key":"253272_CR37","first-page":"1019","volume-title":"IJCAI: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence","author":"J. R. Quinlan","year":"1995","unstructured":"Quinlan, J. R. & Cameron-Jones, R. (1995). Oversearching and layered search in empirical learning. IJCAI: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (pp. 1019\u20131024). San Francisco, CA: Morgan Kaufmann."},{"key":"253272_CR38","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/0890-5401(89)90010-2","volume":"80","author":"J. R. Quinlan","year":"1989","unstructured":"Quinlan, J. R. & Rivest, R. (1989). Inferring decision trees using the minimum description length principle. Information and Computation, 80, 227\u2013248.","journal-title":"Information and Computation"},{"key":"253272_CR39","first-page":"471","volume-title":"Machine Learning: Proceedings of the Twelfth International Conference","author":"R. Rao","year":"1995","unstructured":"Rao, R., Gordon, D., & Spears, W. (1995). For every generalization action, is there really an equal and opposite reaction? Analysis of the conservation law for generalization performance. Machine Learning: Proceedings of the Twelfth International Conference (pp. 471\u2013479). San Francisco, CA: Morgan Kaufmann."},{"key":"253272_CR40","volume-title":"A First Course in Probability","author":"S. Ross","year":"1984","unstructured":"Ross, S. (1984). A First Course in Probability (2nd edition). New York, NY: Macmillan.","edition":"2nd edition"},{"key":"253272_CR41","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1023\/A:1009752403260","volume":"1","author":"S. Salzberg","year":"1997","unstructured":"Salzberg, S. (1997). On comparing classifiers: Pitfalls to avoid and a recommended approach. Data Mining and Knowledge Discovery, 1, 317\u2013328.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"253272_CR42","first-page":"153","volume":"10","author":"C. Schaffer","year":"1993","unstructured":"Schaffer, C. (1993). Overfitting avoidance as bias. Machine Learning, 10, 153\u2013178.","journal-title":"Machine Learning"},{"key":"253272_CR43","first-page":"259","volume-title":"Proceedings of the Eleventh International Conference on Machine Learning","author":"C. Schaffer","year":"1994","unstructured":"Schaffer, C. (1994). A conservation law for generalization performance. Proceedings of the Eleventh International Conference on Machine Learning (pp. 259\u2013265). San Francisco, CA: Morgan Kaufmann."},{"key":"253272_CR44","volume-title":"Searching for Structure (Alias, AID-III); An Approach to Analysis of Substantial Bodies of Micro-Data and Documentation for a Computer Program (Successor to the Automatic Interaction Detector Program)","author":"J. Sonquist","year":"1971","unstructured":"Sonquist, J., Baker, E., & Morgan, J. (1971). Searching for Structure (Alias, AID-III); An Approach to Analysis of Substantial Bodies of Micro-Data and Documentation for a Computer Program (Successor to the Automatic Interaction Detector Program). Ann Arbor, MI: Survey Research Center, Institute for Social Research, The University of Michigan."},{"key":"253272_CR45","volume-title":"Computer Systems That Learn: Classification and Prediction Methods from Statistics, Neural Nets, Machine Learning, and Expert Systems","author":"S. Weiss","year":"1991","unstructured":"Weiss, S. & Kulikowski, C. (1991). Computer Systems That Learn: Classification and Prediction Methods from Statistics, Neural Nets, Machine Learning, and Expert Systems. San Mateo, CA: Morgan Kaufmann."},{"key":"253272_CR46","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/BF00857651","volume":"9","author":"A. White","year":"1995","unstructured":"White, A. & Liu, W. (1995). Superstitious learning and induction. Artificial Intelligence Review, 9, 3\u201318.","journal-title":"Artificial Intelligence Review"},{"key":"253272_CR47","first-page":"47","volume":"6","author":"D Wolpert","year":"1992","unstructured":"Wolpert, D.(1992).On the connection between in-sample testing and generalization error.Complex Systems,6,47\u201394.","journal-title":"Complex Systems"},{"key":"253272_CR48","unstructured":"Wolpert, D.(1994).Off-training set error and a priori distinctions between learning algorithms.Technical Report SFI TR 95\u201301\u2013003. Santa Fe, NM: Santa Fe Institute."}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1023\/A:1007631014630.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1023\/A:1007631014630\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1023\/A:1007631014630.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T11:34:56Z","timestamp":1752147296000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1023\/A:1007631014630"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2000,3]]},"references-count":48,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2000,3]]}},"alternative-id":["253272"],"URL":"https:\/\/doi.org\/10.1023\/a:1007631014630","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2000,3]]},"assertion":[{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}