Machine learning as an experimental science

Langley, Pat·1988·Machine Learning
DOI 10.1007/bf00115008

Cited by (187)

Items 101–187 of 187

  1. Making Sense of Machine Learning: Integrating Youth’s Conceptual, Creative, and Critical Understandings of AI
    Luis Morales‐Navarro, Yasmin B. Kafai, Francisco Barnés De Castro, William D. Payne, Kayla DesPortes, Daniella DiPaola, Randi Williams, Safinah Ali, Cynthia Breazeal, Clifford Lee et al. · 2023 · Proceedings.
  2. sequential Instance-Based Learning for Planning in the Context of an Imperfect Information Game
    Jenngang Shih · 2001 · Lecture notes in computer science
  3. Acquisition and improvement of human motor skills: learning through observation and practice
    Wayne Iba, Patrick Langley · 1991 · NASA Technical Reports Server (NASA)
  4. Tools and Techniques for Decision Tree Learning
    Tapio Elomaa · 1996 · Työväentutkimus Vuosikirja
  5. Progressing Towards Responsible AI
    Teresa Scantamburlo, Àtia Cortés, Marie Schacht · 2020 · arXiv (Cornell University)
  6. Feature interval learning algorithms for classification
    Aynur A. Dayanik · 2010 · Knowledge-Based Systems
  7. Characterising Confounding Effects in Music Classification Experiments through Interventions
    Francisco Rodríguez-Algarra, Bob L. T. Sturm, Simon Dixon · 2019 · Transactions of the International Society for Music Information Retrieval
  8. SweetPea: A standard language for factorial experimental design
    Sebastian Musslick, Anastasia Cherkaev, Ben Draut, Ahsan Sajjad Butt, Pierce Darragh, Vivek Srikumar, Matthew Flatt, Jonathan D. Cohen · 2021 · Behavior Research Methods
  9. A comparison of the utility of data mining algorithms in an open distance learning context
    Angelo Fynn, Jaroslaw Adamiak · 2018 · South African Journal of Higher Education
  10. A Genetic Algorithm Approach for Creating Neural Network Ensembles
    AMANDA J. C. SHARKEY · 1999 · Perspectives in neural computing
  11. Automatic goal extraction from user actions to accelerate the browsing of software libraries.
    C. Drummond · 1993
  12. Improved empirical methods in reinforcement-learning evaluation
    Vukosi N. Marivate · 2015
  13. "Seleção de atributos importantes para a extração de conhecimento de bases de dados"
    Huei Lee · 2005 · Digital Library of Theses and Dissertations (Universidade de São Paulo)
  14. How Mature Is the Field of Machine Learning?
    Marcello Pelillo, Teresa Scantamburlo · 2013 · Lecture notes in computer science
  15. Improving Invoice Allocation in Accounting—An Account Recommender Case Study Applying Machine Learning
    Markus Eßwein, Jöerg Mayer, Diana Sedneva, Daniel Pagels, Jean-Paul Albers · 2020 · Lecture notes in information systems and organisation
  16. Paradigms for machine learning
    Jeffrey C. Schlimmer, Pat Langley · 1991
  17. Lazy Acquisition of Place Knowledge
    Pat Langley, Karl Pfleger, Mehran Sahami · 1997 · Artificial Intelligence Review
  18. Annotated bibliography on research methodologies
    Yoram Reich · 1994 · Artificial intelligence for engineering design analysis and manufacturing
  19. Declarative Data Generation with ProbLog
    Anton Dries · 2015 · International Symposium on Information and Communication Technology
  20. Air Traffic Flow Management Data Mining and Analysis for In-flight Cost Optimization
    Leonardo L. B. V. Cruciol, Li Weigang, John-Paul Clarke, Leihong Li · 2015 · Computational methods in applied sciences
  21. Determining appropriate membership functions to simplify fuzzy induction
    Tzung‐Pei Hong, Shyue-Liang Wang · 2000 · Intelligent Data Analysis
  22. Introduction to the special issue on empirical evaluations in reinforcement learning
    Shimon Whiteson, Michael L. Littman · 2011 · Machine Learning
  23. Generating the ground truth: Synthetic data for soft label and label noise research
    Sjoerd de Vries, Dirk Thierens · 2025 · International Journal of Data Science and Analytics
  24. On Building Decision Trees from Large-scale Data in Applications of On-line Advertising
    Shivaram Kalyanakrishnan, Deepthi Singh, Ravi Kant · 2014 · ACM International Conference on Information and Knowledge Management (CIKM)
  25. Pattern recognition between science and engineering: A red herring?
    Marcello Pelillo, Teresa Scantamburlo, Viola Schiaffonati · 2015 · Pattern Recognition Letters
  26. The Case Against Registered Reports
    Odd Erik Gundersen · 2021 · AI Magazine
  27. Reinforcement Learning
    Christopher J. Gatti · 2014 · Springer theses
  28. Is the Best Better? Bayesian Statistical Model Comparison for Natural Language Processing
    Piotr Szymański, Kyle Gorman · 2020 · Conference on Empirical Methods in Natural Language Processing (EMNLP)
  29. Automatic inference of causal reasoning chains from student essays
    Simon Hughes · 2019 · Digital Commons-DePaul (DePaul University)
  30. Pareto Cooperative-Competitive Genetic Programming: A Classification Benchmarking Study
    Andrew R. McIntyre, Malcolm Iain Heywood · 2008 · Genetic and evolutionary computation
  31. Philosophical aspects in pattern recognition research
    Teresa Scantamburlo · 2014 · ARCA (Università Ca' Foscari Venezia)
  32. Sample compression, margins and generalization: Extensions to the set covering machine
    Mohak Shah · 2006 · uO Research (University of Ottawa)
  33. Accelerating browsing by automatically inferring a user's search goal
    Chris Drummond, Robert C. Holte, Dan Ionescu · 1993 · Knowledge-Based Software Engineering Conference (KBSE)
  34. Robotic learning from distributed sensory sources
    François G. Pin, P. Belmans, Susan I. Hruska, Carl W. Steidley, Lynne E. Parker · 1991 · IEEE Transactions on Systems Man and Cybernetics
  35. Systematic Evaluation of Design Decisions in CBR Systems
    Juan Carlos Santamaria, Ashwin Ram · 1994
  36. Agents of Exploration and Discovery
    Pat Langley · 2021 · AI Magazine
  37. Data Mining of Design Products and Processes
    Yoram Reich · 2006 · Springer eBooks
  38. On the Noise Resilience of Ranking Measures
    Daniel Berrar · 2016 · Lecture notes in computer science
  39. Evaluation with uncertainty
    Gaya K. Jayasinghe · 2015 · RMIT Research Repository (RMIT University Library)
  40. Analisando os dados do programa de melhoramento genético da raça nelore com data warehousing e data mining.
    Valmir Ferreira Marques · 2002 · Digital Library of Theses and Dissertations (Universidade de São Paulo)
  41. Learning Unification-Based Natural Language Grammars
    Miles Osborne · 1995 · arXiv (Cornell University)
  42. On the Metric-based Approach to Supervised Concept Learning
    Niklas Lavesson · 2008
  43. The role of experimentation in artificial intelligence
    Bruce G. Buchanan · 1994 · Philosophical Transactions of the Royal Society of London Series A Physical and Engineering Sciences
  44. Chatbots in Telemedicine
    Sudhair Abbas Bangash, Syed Sikandar Shah, Muhammad Ali Adam, M. Naseer A. Khan, Munir Ahmad · 2024 · Advances in computer and electrical engineering book series
  45. Alzheimer's Disease Stage Prediction using Machine Learning and Multi Agent System
    Henok Wordoffa, Ezedin Wangoria · 2012
  46. It's time for your evaluation
    Kai D. Knight · 1996 · IEEE Expert
  47. A learning approach to processor allocation in parallel systems
    Amy Apon, Thomas D. Wagner, Lawrence W. Dowdy · 1999 · ACM International Conference on Information and Knowledge Management (CIKM)
  48. The NCTU BioInfo Archive of biological data sets for bioinformatics research and experimentation
    Yuh‐Jyh Hu · 2002 · Bioinformatics
  49. Machine Learning and Artificial Intelligence in Cardiovascular Imaging
    Marwen H. Eid, James V. Spearman, Marly van Assen, Domenico De Santis, Pooyan Sahbaee, Scott P. Landreth, Brian E. Jacobs, Carlo Nicola De Cecco · 2019 · Contemporary medical imaging
  50. On the use of multi-objective evolutionary algorithms for classification rule induction
    Christian Setzkorn · 2005 · OpenGrey (Institut de l'Information Scientifique et Technique)
  51. Requirements for Configurer Tests: A Position Statement
    David C. Brown · 1999
  52. Inference and learning in Bayesian networks using overlapping swarm intelligence
    Nathan Fortier · 2015 · Montana State University ScholarWorks (Montana State University)
  53. Cellular and Wi-Fi technologies evolution: from complementarity to competition
    Biljana Bojović · 2022
  54. Bio-Measurements Estimation and Support in Knee Recovery through Machine Learning
    Bernardino, João, Teixeira, Luís Filipe, Ferreira, Hugo Sereno · 2018 · arXiv (Cornell University)
  55. Analisis Active learning SVM berbasis Margin Sampling pada Sentimen YouTube MBG
    Minarwati, Alvian Putra Hardiadi · 2026 · Jurnal Informatika Komputer Bisnis dan Manajemen
  56. Neural Agent for Text Database Discovery
    Yong Suk Choi · 2003 · Studies in fuzziness and soft computing
  57. Mind the Gap: Confronting the Vast Divide Between CS Teaching and Machine Learning Pedagogy
    Shai Perach, Giora Alexandron · 2024 · Lecture notes in computer science
  58. The Outcomes and Publication Standards of Research Descriptions in Document Classification: A Systematic Review
    Marcin Mirończuk, Adam Müller, Witold Pedrycz C · 2024 · IEEE Access
  59. APPrOVE: Application-oriented validation and evaluation of supervised learners
    Niklas Lavesson, Paul Davidsson · 2010 · IEEE International Conference on Intelligent Systems
  60. A Study on Machine Learning: Elements, Characteristics and Algorithms
    K. Chokkanathan, S. Koteeswaran · 2018 · International Journal of Engineering & Technology
  61. Convolutional neural network model for Augmentation Index prediction based on photoplethysmography
    David Perpetuini, Chiara Filippini, Antonio Maria Chiarelli, Daniela Cardone, Sergio Rinella, Simona Massimino, Francesco Bianco, Valentina Bucciarelli, Vincenzo Vinciguerra, Piero Giorgio Fallica et al. · 2021 · Infrared Sensors, Devices, and Applications
  62. Development and Validation of Accelerometer-Based Activity Classification Algorithms for Older Adults: A Machine Learning Approach
    Jeffer Eidi Sasaki · 2021 · Scholarworks (University of Massachusetts Amherst)
  63. Learning by observation and active experimentation in a knowledge based CAD-environment
    Klaus Milzner, B. Leifhelm · 2003 · IEEE Computer Society European Conference (CompEuro)
  64. Systematic Experimentation with Deductive Learning: Satisficing vs. Optimizing search
    Shaul Markovitch · 2004
  65. Getting Things in Order: Collecting and Analyzing Data on Learning
    Frank E. Ritter, Josef Nerb, Erno Lehtinen · 2007 · Oxford University Press eBooks
  66. Redes Bayesianas para Extração de Conhecimento de Bases de Dados, Considerando a Incorporação de Conhecimento de Fundo e o Tratamento de Dados Incompletos
    Cláudio Alex Jorge da Rocha · 2018 · Digital Library of Theses and Dissertations (Universidade de São Paulo)
  67. Learning Concepts by Arranging Appropriate Training Order
    Yao-Tung Hsu, Tzung‐Pei Hong, Shian‐Shyong Tseng · 2001 · Minds and Machines
  68. Combinação de classificadores simbólicos utilizando medidas de regras de conhecimento e algoritmos genéticos
    Flávia Bernardini · 2006 · Digital Library of Theses and Dissertations (Universidade de São Paulo)
  69. Clasificación automática basada en análisis espectral
    Gregorio Perichinsky · 2007
  70. Learning performance estimations in a knowledge based CAD-environment
    Klaus Milzner · 2005 · Springer eBooks
  71. Hierarchical Multi-agent Organization for Text Database Discovery
    Yong Suk Choi, Jaeho Lee, Suk In Yoo · 1999 · Lecture notes in computer science
  72. Design of Hybrid Unsupervised-Supervised Classifier for Automatic Emotion Recognition
    Jee‐Eun Lee, Sun Kook Yoo · 2014 · The Transactions of The Korean Institute of Electrical Engineers
  73. A next generation Space Shuttle concept
    HUBERT DAVIS, Charles Teixeira · 1989 · AIAA Aerospace Sciences Meeting
  74. TEACHERS' AND ADMINISTRATORS' PERCEPTIONS OF THE UNDER- REPRESENTATION OF AFRICAN AMERICAN MALES IN GIFTED AND TALENTED EDUCATION PROGRAMS
    Roy D. Sermons · 2016 · Digital Commons (Liberty University)
  75. An Adaptive Non-parametric Kernel Method for Classification
    Gregory John Kaszycki · 2000 · NCSU Libraries Repository (North Carolina State University Libraries)
  76. Some General Results On Overfitting In Machine Learning
    Antony Van der Mude · 2017 · viXra
  77. A System for Managing Experiments in Data Mining
    Greeshma Myneni · 2010 · OhioLink ETD Center (Ohio Library and Information Network)
  78. Descrição da arquitetura e do projeto do sistema computacional GAERE para realizar evolução genética de classificadores simbólicos.
    Flávia Bernardini, Maria Carolina Monard · 2006
  79. Machine learning
    Pedro Domingos · 2002
  80. Learning with Regularization Networks
    Petra Kudová · 2007
  81. Optimization of intrusion detection systems based on machine learning for cybersecurity by boosting feature engineering and model selection techniques
    Xavier Andrés Larriva Novo · 2021
  82. BIBLIOGRAPHY OF RECENT MACHINE LEARNING RESEARCH 1985–1989
    1990 · Elsevier eBooks
  83. Lazy Acquisition of Place Knowledge
    Pat Langley, Karl Pfleger, Mehran Sahami · 1997 · Springer eBooks
  84. Aircraft detection using single shot scale-invariant face detector with viridis saliency map from remote sensing image
    Teepakorn Lilek · 2019
  85. Yapay Zekâ ve Vergi Uygulamaları: ChatGPT’nin Kullanım Alanları, Etkileri ve Etik Zorluklar
    Hakan Özdemir · 2025 · Fiscaoeconomia
  86. Methodology for Design and Analysis of Machine Learning Competitions
    Adrien Pavão · 2023 · theses.fr (ABES)
  87. Irredundant k-fold cross-validation for reliable, scalable, and energy-efficient model evaluation
    Jesús S. Aguilar–Ruiz · 2026 · Machine Learning with Applications