Back propagation is sensitive to initial conditions
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Note on free lunches and cross-validation
Neural Computation
Algorithmic stability and sanity-check bounds for leave-one-out cross-validation
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
No free lunch for cross-validation
Neural Computation
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
An introduction to variable and feature selection
The Journal of Machine Learning Research
Use of the zero norm with linear models and kernel methods
The Journal of Machine Learning Research
Ensembles of nested dichotomies for multi-class problems
ICML '04 Proceedings of the twenty-first international conference on Machine learning
No Unbiased Estimator of the Variance of K-Fold Cross-Validation
The Journal of Machine Learning Research
Evolutionary approaches to fuzzy modelling for classification
The Knowledge Engineering Review
Machine Learning
Machine Learning
Predicting Students' Marks in Hellenic Open University
ICALT '05 Proceedings of the Fifth IEEE International Conference on Advanced Learning Technologies
Closed-form dual perturb and combine for tree-based models
ICML '05 Proceedings of the 22nd international conference on Machine learning
Local bagging of decision stumps
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Machine Learning
Classification using Hierarchical Naïve Bayes models
Machine Learning
Pruning in ordered bagging ensembles
ICML '06 Proceedings of the 23rd international conference on Machine learning
Feature subset selection bias for classification learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Rotation Forest: A New Classifier Ensemble Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local averaging of heterogeneous regression models
International Journal of Hybrid Intelligent Systems
Local voting of weak classifiers
International Journal of Knowledge-based and Intelligent Engineering Systems
Diagnosing scrapie in sheep: A classification experiment
Computers in Biology and Medicine
Mining optimal decision trees from itemset lattices
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Adaptive fuzzy modeling versus artificial neural networks
Environmental Modelling & Software
Machine learning: a review of classification and combining techniques
Artificial Intelligence Review
Predicting defect-prone software modules using support vector machines
Journal of Systems and Software
Boosting recombined weak classifiers
Pattern Recognition Letters
RotBoost: A technique for combining Rotation Forest and AdaBoost
Pattern Recognition Letters
Genetic local search for rule learning
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers
The Journal of Machine Learning Research
Class-switching neural network ensembles
Neurocomputing
An Empirical Comparison of Exact Nearest Neighbour Algorithms
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
Fuzzy Evolutionary Probabilistic Neural Networks
ANNPR '08 Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition
Top-Down Hierarchical Ensembles of Classifiers for Predicting G-Protein-Coupled-Receptor Functions
BSB '08 Proceedings of the 3rd Brazilian symposium on Bioinformatics: Advances in Bioinformatics and Computational Biology
Using the Bottom Clause and Mode Declarations on FOL Theory Revision from Examples
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Split Criterions for Variable Selection Using Decision Trees
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Combining Decision Trees Based on Imprecise Probabilities and Uncertainty Measures
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees
DS '08 Proceedings of the 11th International Conference on Discovery Science
Revisiting Multiple-Instance Learning Via Embedded Instance Selection
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Multiclass Boosting Algorithms for Shrinkage Estimators of Class Probability
IEICE - Transactions on Information and Systems
LEGAL-tree: a lexicographic multi-objective genetic algorithm for decision tree induction
Proceedings of the 2009 ACM symposium on Applied Computing
HTILDE: scaling up relational decision trees for very large databases
Proceedings of the 2009 ACM symposium on Applied Computing
Supervised machine learning algorithms for protein structure classification
Computational Biology and Chemistry
Rule learning with monotonicity constraints
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
The multi-label OCS with a genetic algorithm for rule discovery: implementation and first results
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Target Identification from High Resolution Remote Sensing Image by Combining Multiple Classifiers
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Learning Rule Ensembles for Ordinal Classification with Monotonicity Constraints
Fundamenta Informaticae - Fundamentals of Knowledge Technology
Classifier Chains for Multi-label Classification
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Feature Selection by Transfer Learning with Linear Regularized Models
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Microarray analysis of autoimmune diseases by machine learning procedures
IEEE Transactions on Information Technology in Biomedicine
Rotation-based model trees for classification
International Journal of Data Analysis Techniques and Strategies
CIBCB'09 Proceedings of the 6th Annual IEEE conference on Computational Intelligence in Bioinformatics and Computational Biology
Conditional Density Estimation with Class Probability Estimators
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Averaged Naive Bayes Trees: A New Extension of AODE
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Cascade generalisation for ordinal problems
International Journal of Artificial Intelligence and Soft Computing
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
An experimental study on rotation forest ensembles
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Evolutionary model tree induction
Proceedings of the 2010 ACM Symposium on Applied Computing
Out of bootstrap estimation of generalization error curves in bagging ensembles
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Artificial Intelligence in Medicine
Lexicographic multi-objective evolutionary induction of decision trees
International Journal of Bio-Inspired Computation
Optimal constraint-based decision tree induction from itemset lattices
Data Mining and Knowledge Discovery
Selecting few genes for microarray gene expression classification
CAEPIA'09 Proceedings of the Current topics in artificial intelligence, and 13th conference on Spanish association for artificial intelligence
Evolutionary model trees for handling continuous classes in machine learning
Information Sciences: an International Journal
Random one-dependence estimators
Pattern Recognition Letters
Speeding up and boosting diverse density learning
DS'10 Proceedings of the 13th international conference on Discovery science
Rotation forest on microarray domain: PCA versus ICA
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Ensemble methods and model based diagnosis using possible conflicts and system decomposition
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Learning random forests for ranking
Frontiers of Computer Science in China
One Dependence Value Difference Metric
Knowledge-Based Systems
Defect prediction using social network analysis on issue repositories
Proceedings of the 2011 International Conference on Software and Systems Process
Hybrid feature selection method for supervised classification based on Laplacian score ranking
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
Fast projection pursuit based on quality of projected clusters
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
Class imbalance methods for translation initiation site recognition in DNA sequences
Knowledge-Based Systems
Translation initiation site recognition by means of evolutionary response surfaces
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
Hubness-based fuzzy measures for high-dimensional k-nearest neighbor classification
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
Correcting bias in statistical tests for network classifier evaluation
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
GRASP forest: a new ensemble method for trees
MCS'11 Proceedings of the 10th international conference on Multiple classifier systems
A comparison of two strategies for scaling up instance selection in huge datasets
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
Ensemble logistic regression for feature selection
PRIB'11 Proceedings of the 6th IAPR international conference on Pattern recognition in bioinformatics
Naive bayes for text classification with unbalanced classes
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Improving on bagging with input smearing
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Bagging model trees for classification problems
PCI'05 Proceedings of the 10th Panhellenic conference on Advances in Informatics
Local additive regression of decision stumps
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
Ensembles of balanced nested dichotomies for multi-class problems
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Unsupervised discretization using tree-based density estimation
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Improving Tree augmented Naive Bayes for class probability estimation
Knowledge-Based Systems
A GMDH-based fuzzy modeling approach for constructing TS model
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
Learning Instance Weighted Naive Bayes from labeled and unlabeled data
Journal of Intelligent Information Systems
Bagging random trees for estimation of tissue softness
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
Expert Systems with Applications: An International Journal
A latent model for collaborative filtering
International Journal of Approximate Reasoning
Learning naïve bayes tree for conditional probability estimation
AI'06 Proceedings of the 19th international conference on Advances in Artificial Intelligence: Canadian Society for Computational Studies of Intelligence
Multivariate statistical tests for comparing classification algorithms
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Beyond trees: adopting MITI to learn rules and ensemble classifiers for multi-instance data
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
A Modified Short and Fukunaga Metric based on the attribute independence assumption
Pattern Recognition Letters
Not so greedy: Randomly Selected Naive Bayes
Expert Systems with Applications: An International Journal
Predicting software maintenance effort through evolutionary-based decision trees
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Simple incremental instance selection wrapper for classification
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Resampling methods for meta-model validation with recommendations for evolutionary computation
Evolutionary Computation
A structural cluster kernel for learning on graphs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning a concept-based document similarity measure
Journal of the American Society for Information Science and Technology
Learning theories using estimation distribution algorithms and (reduced) bottom clauses
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Learning Rule Ensembles for Ordinal Classification with Monotonicity Constraints
Fundamenta Informaticae - Fundamentals of Knowledge Technology
Design and Analysis of Classifier Learning Experiments in Bioinformatics: Survey and Case Studies
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Environmental Modelling & Software
Model selection based product kernel learning for regression on graphs
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Software effort prediction: a hyper-heuristic decision-tree based approach
Proceedings of the 28th Annual ACM Symposium on Applied Computing
An Augmented Value Difference Measure
Pattern Recognition Letters
Towards minimizing the annotation cost of certified text classification
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Pattern Recognition
Aircraft taxi time prediction: Comparisons and insights
Applied Soft Computing
Information Sciences: an International Journal
The influence of global constraints on similarity measures for time-series databases
Knowledge-Based Systems
Benchmarking local classification methods
Computational Statistics
A hybrid decision tree classifier
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In order to compare learning algorithms, experimental results reported in the machine learning literature often use statistical tests of significance to support the claim that a new learning algorithm generalizes better. Such tests should take into account the variability due to the choice of training set and not only that due to the test examples, as is often the case. This could lead to gross underestimation of the variance of the cross-validation estimator, and to the wrong conclusion that the new algorithm is significantly better when it is not. We perform a theoretical investigation of the variance of a variant of the cross-validation estimator of the generalization error that takes into account the variability due to the randomness of the training set as well as test examples. Our analysis shows that all the variance estimators that are based only on the results of the cross-validation experiment must be biased. This analysis allows us to propose new estimators of this variance. We show, via simulations, that tests of hypothesis about the generalization error using those new variance estimators have better properties than tests involving variance estimators currently in use and listed in Dietterich (1998). In particular, the new tests have correct size and good power. That is, the new tests do not reject the null hypothesis too often when the hypothesis is true, but they tend to frequently reject the null hypothesis when the latter is false.