A collection of research papers on decision, classification and regression trees with implementations.
A curated list of classification and regression tree research papers with implementations from the following conferences:
Similar collections about graph classification, gradient boosting, fraud detection, Monte Carlo tree search, and community detection papers with implementations.
Using MaxSAT for Efficient Explanations of Tree Ensembles (AAAI 2022)
FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles (AAAI 2022)
Explainable and Local Correction of Classification Models Using Decision Trees (AAAI 2022)
Robust Optimal Classification Trees against Adversarial Examples (AAAI 2022)
Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values (AAAI 2022)
Fast Sparse Decision Tree Optimization via Reference Ensembles (AAAI 2022)
TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion (AAAI 2022)
Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision Trees (AISTATS 2022)
Accurate Shapley Values for explaining tree-based models (AISTATS 2022)
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds (AISTATS 2022)
Enterprise-Scale Search: Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees (WWW 2022)
MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration (WWW 2022)
Rethinking Conversational Recommendations: Is Decision Tree All You Need (CIKM 2022)
A Neural Tangent Kernel Perspective of Infinite Tree Ensembles (ICLR 2022)
POETREE: Interpretable Policy Learning with Adaptive Decision Trees (ICLR 2022)
Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models (ICML 2022)
Popular decision tree algorithms are provably noise tolerant (ICML 2022)
Robust Counterfactual Explanations for Tree-Based Ensembles (ICML 2022)
Fast Provably Robust Decision Trees and Boosting (ICML 2022)
BAMDT: Bayesian Additive Semi-Multivariate Decision Trees for Nonparametric Regression (ICML 2022)
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features (ICML 2022)
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources (ICML 2022)
On Preferred Abductive Explanations for Decision Trees and Random Forests (IJCAI 2022)
Extending Decision Tree to Handle Multiple Fairness Criteria (IJCAI 2022)
Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles (KDD 2022)
Integrity Authentication in Tree Models (KDD 2022)
Retrieval-Based Gradient Boosting Decision Trees for Disease Risk Assessment (KDD 2022)
Improved feature importance computation for tree models based on the Banzhaf value (UAI 2022)
Learning linear non-Gaussian polytree models (UAI 2022)
Online Probabilistic Label Trees (AISTATS 2021)
Optimal Decision Trees for Nonlinear Metrics (AAAI 2021)
SAT-based Decision Tree Learning for Large Data Sets (AAAI 2021)
Parameterized Complexity of Small Decision Tree Learning (AAAI 2021)
Counterfactual Explanations for Oblique Decision Trees: Exact - Efficient Algorithms (AAAI 2021)
Geometric Heuristics for Transfer Learning in Decision Trees (CIKM 2021)
Fairness-Aware Training of Decision Trees by Abstract Interpretation (CIKM 2021)
Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification (CIKM 2021)
Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees (ICLR 2021)
NBDT: Neural-Backed Decision Tree (ICLR 2021)
Versatile Verification of Tree Ensembles (ICML 2021)
Connecting Interpretability and Robustness in Decision Trees through Separation (ICML 2021)
Optimal Counterfactual Explanations in Tree Ensembles (ICML 2021)
Efficient Training of Robust Decision Trees Against Adversarial Examples (ICML 2021)
Learning Binary Decision Trees by Argmin Differentiation (ICML 2021)
BLOCKSET (Block-Aligned Serialized Trees): Reducing Inference Latency for Tree ensemble Deployment (KDD 2021)
ControlBurn: Feature Selection by Sparse Forests (KDD 2021)
Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression (KDD 2021)
Verifying Tree Ensembles by Reasoning about Potential Instances (SDM 2021)
DTCA: Decision Tree-based Co-Attention Networks for Explainable Claim Verification (ACL 2020)
Privacy-Preserving Gradient Boosting Decision Trees (AAAI 2020)
Practical Federated Gradient Boosting Decision Trees (AAAI 2020)
Efficient Inference of Optimal Decision Trees (AAAI 2020)
Learning Optimal Decision Trees Using Caching Branch-and-Bound Search (AAAI 2020)
Abstract Interpretation of Decision Tree Ensemble Classifiers (AAAI 2020)
Scalable Feature Selection for (Multitask) Gradient Boosted Trees (AISTATS 2020)
Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning (AISTATS 2020)
Exploiting Categorical Structure Using Tree-Based Methods (AISTATS 2020)
LdSM: Logarithm-depth Streaming Multi-label Decision Trees (AISTATS 2020)
Oblique Decision Trees from Derivatives of ReLU Networks (ICLR 2020)
Provable Guarantees for Decision Tree Induction: the Agnostic Setting (ICML 2020)
Decision Trees for Decision-Making under the Predict-then-Optimize Framework (ICML 2020)
The Tree Ensemble Layer: Differentiability meets Conditional Computation (ICML 2020)
Generalized and Scalable Optimal Sparse Decision Trees (ICML 2020)
Born-Again Tree Ensembles (ICML 2020)
On Lp-norm Robustness of Ensemble Decision Stumps and Trees (ICML 2020)
Smaller, More Accurate Regression Forests Using Tree Alternating Optimization (ICML 2020)
Learning Optimal Decision Trees with MaxSAT and its Integration in AdaBoost (IJCAI 2020)
Speeding up Very Fast Decision Tree with Low Computational Cost (IJCAI 2020)
PyDL8.5: a Library for Learning Optimal Decision Trees (IJCAI 2020)
Geodesic Forests (KDD 2020)
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees (NeurIPS 2020)
Estimating Decision Tree Learnability with Polylogarithmic Sample Complexity (NeurIPS 2020)
Universal Guarantees for Decision Tree Induction via a Higher-Order Splitting Criterion (NeurIPS 2020)
Smooth And Consistent Probabilistic Regression Trees (NeurIPS 2020)
An Efficient Adversarial Attack for Tree Ensembles (NeurIPS 2020)
Decision Trees as Partitioning Machines to Characterize their Generalization Properties (NeurIPS 2020)
Evidence Weighted Tree Ensembles for Text Classification (SIGIR 2020)
Multi Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System (AAAI 2019)
Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME (AAAI 2019)
Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making (AAAI 2019)
Desiderata for Interpretability: Explaining Decision Tree Predictions with Counterfactuals (AAAI 2019)
Weighted Oblique Decision Trees (AAAI 2019)
Learning Optimal Classification Trees Using a Binary Linear Program Formulation (AAAI 2019)
Optimization of Hierarchical Regression Model with Application to Optimizing Multi-Response Regression K-ary Trees (AAAI 2019)
XBART: Accelerated Bayesian Additive Regression Trees (AISTATS 2019)
Interaction Detection with Bayesian Decision Tree Ensembles (AISTATS 2019)
Adversarial Training of Gradient-Boosted Decision Trees (CIKM 2019)
Interpretable MTL from Heterogeneous Domains using Boosted Tree (CIKM 2019)
Interpreting CNNs via Decision Trees (CVPR 2019)
EDiT: Interpreting Ensemble Models via Compact Soft Decision Trees (ICDM 2019)
Fair Adversarial Gradient Tree Boosting (ICDM 2019)
Functional Transparency for Structured Data: a Game-Theoretic Approach (ICML 2019)
Incorporating Grouping Information into Bayesian Decision Tree Ensembles (ICML 2019)
Adaptive Neural Trees (ICML 2019)
Robust Decision Trees Against Adversarial Examples (ICML 2019)
Learn Smart with Less: Building Better Online Decision Trees with Fewer Training Examples (IJCAI 2019)
FAHT: An Adaptive Fairness-aware Decision Tree Classifier (IJCAI 2019)
Inter-node Hellinger Distance based Decision Tree (IJCAI 2019)
Gradient Boosting with Piece-Wise Linear Regression Trees (IJCAI 2019)
A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees (IJCAI 2019)
Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search (KDD 2019)
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers (NeurIPS 2019)
Partitioning Structure Learning for Segmented Linear Regression Trees (NeurIPS 2019)
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks (NeurIPS 2019)
Optimal Decision Tree with Noisy Outcomes (NeurIPS 2019)
Regularized Gradient Boosting (NeurIPS 2019)
Optimal Sparse Decision Trees (NeurIPS 2019)
MonoForest framework for tree ensemble analysis (NeurIPS 2019)
Calibrating Probability Estimation Trees using Venn-Abers Predictors (SDM 2019)
Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization (SDM 2019)
Forest Packing: Fast Parallel, Decision Forests (SDM 2019)
Block-distributed Gradient Boosted Trees (SIGIR 2019)
Entity Personalized Talent Search Models with Tree Interaction Features (WWW 2019)
Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees (AAAI 2018)
MERCS: Multi-Directional Ensembles of Regression and Classification Trees (AAAI 2018)
Differential Performance Debugging With Discriminant Regression Trees (AAAI 2018)
Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction (AAAI 2018)
MDP-Based Cost Sensitive Classification Using Decision Trees (AAAI 2018)
Generative Adversarial Image Synthesis With Decision Tree Latent Controller (CVPR 2018)
Enhancing Very Fast Decision Trees with Local Split-Time Predictions (ICDM 2018)
Realization of Random Forest for Real-Time Evaluation through Tree Framing (ICDM 2018)
Finding Influential Training Samples for Gradient Boosted Decision Trees (ICML 2018)
Learning Optimal Decision Trees with SAT (IJCAI 2018)
Extremely Fast Decision Tree (KDD 2018)
RapidScorer: Fast Tree Ensemble Evaluation by Maximizing Compactness in Data Level Parallelization (KDD 2018)
CatBoost: Unbiased Boosting with Categorical Features (NIPS 2018)
Active Learning for Non-Parametric Regression Using Purely Random Trees (NIPS 2018)
Alternating Optimization of Decision Trees with Application to Learning Sparse Oblique Trees (NIPS 2018)
Multi-Layered Gradient Boosting Decision Trees (NIPS 2018)
Transparent Tree Ensembles (SIGIR 2018)
Privacy-aware Ranking with Tree Ensembles on the Cloud (SIGIR 2018)
Strategic Sequences of Arguments for Persuasion Using Decision Trees (AAAI 2017)
BoostVHT: Boosting Distributed Streaming Decision Trees (CIKM 2017)
Latency Reduction via Decision Tree Based Query Construction (CIKM 2017)
Enumerating Distinct Decision Trees (ICML 2017)
Gradient Boosted Decision Trees for High Dimensional Sparse Output (ICML 2017)
Consistent Feature Attribution for Tree Ensembles (ICML 2017)
Extremely Fast Decision Tree Mining for Evolving Data Streams (KDD 2017)
CatBoost: Gradient Boosting with Categorical Features Support (NIPS 2017)
LightGBM: A Highly Efficient Gradient Boosting Decision Tree (NIPS 2017)
Variable Importance Using Decision Trees (NIPS 2017)
A Unified Approach to Interpreting Model Predictions (NIPS 2017)
Pruning Decision Trees via Max-Heap Projection (SDM 2017)
A Practical Method for Solving Contextual Bandit Problems Using Decision Trees (UAI 2017)
Complexity of Solving Decision Trees with Skew-Symmetric Bilinear Utility (UAI 2017)
GB-CENT: Gradient Boosted Categorical Embedding and Numerical Trees (WWW 2017)
Sparse Perceptron Decision Tree for Millions of Dimensions (AAAI 2016)
Learning Online Smooth Predictors for Realtime Camera Planning Using Recurrent Decision Trees (CVPR 2016)
Online Learning with Bayesian Classification Trees (CVPR 2016)
Accurate Robust and Efficient Error Estimation for Decision Trees (ICML 2016)
Meta-Gradient Boosted Decision Tree Model for Weight and Target Learning (ICML 2016)
Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments (KDD 2016)
XGBoost: A Scalable Tree Boosting System (KDD 2016)
Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale (NIPS 2016)
A Communication-Efficient Parallel Algorithm for Decision Tree (NIPS 2016)
Exploiting CPU SIMD Extensions to Speed-up Document Scoring with Tree Ensembles (SIGIR 2016)
Post-Learning Optimization of Tree Ensembles for Efficient Ranking (SIGIR 2016)
Particle Gibbs for Bayesian Additive Regression Trees (AISTATS 2015)
DART: Dropouts Meet Multiple Additive Regression Trees (AISTATS 2015)
Single Target Tracking Using Adaptive Clustered Decision Trees and Dynamic Multi-level Appearance Models (CVPR 2015)
Face Alignment Using Cascade Gaussian Process Regression Trees (CVPR 2015)
Tracking-by-Segmentation with Online Gradient Boosting Decision Tree (ICCV 2015)
Entropy Evaluation Based on Confidence Intervals of Frequency Estimates : Application to the Learning of Decision Trees (ICML 2015)
Large-scale Distributed Dependent Nonparametric Trees (ICML 2015)
Optimal Action Extraction for Random Forests and Boosted Trees (KDD 2015)
A Decision Tree Framework for Spatiotemporal Sequence Prediction (KDD 2015)
Efficient Non-greedy Optimization of Decision Trees (NIPS 2015)
QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees (SIGIR 2015)
A Mixtures-of-Trees Framework for Multi-Label Classification (CIKM 2014)
On Building Decision Trees from Large-scale Data in Applications of On-line Advertising (CIKM 2014)
Fast Supervised Hashing with Decision Trees for High-Dimensional Data (CVPR 2014)
One Millisecond Face Alignment with an Ensemble of Regression Trees (CVPR 2014)
The return of AdaBoost.MH: multi-class Hamming trees (ICLR 2014)
Diagnosis Determination: Decision Trees Optimizing Simultaneously Worst and Expected Testing Cost (ICML 2014)
Learning Multiple-Question Decision Trees for Cold-Start Recommendation (WSDM 2013)
Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria (ICCV 2013)
Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees (ICCV 2013)
Conformal Prediction Using Decision Trees (ICDM 2013)
Focal-Test-Based Spatial Decision Tree Learning: A Summary of Results (ICDM 2013)
Top-down Particle Filtering for Bayesian Decision Trees (ICML 2013)
Quickly Boosting Decision Trees - Pruning Underachieving Features Early (ICML 2013)
Knowledge Compilation for Model Counting: Affine Decision Trees (IJCAI 2013)
Understanding Variable Importances in Forests of Randomized Trees (NIPS 2013)
Regression-tree Tuning in a Streaming Setting (NIPS 2013)
Learning Max-Margin Tree Predictors (UAI 2013)
Regression Tree Fields - An Efficient, Non-parametric Approach to Image Labeling Problems (CVPR 2012)
ConfDTree: Improving Decision Trees Using Confidence Intervals (ICDM 2012)
Improved Information Gain Estimates for Decision Tree Induction (ICML 2012)
Learning Partially Observable Models Using Temporally Abstract Decision Trees (NIPS 2012)
Subtree Replacement in Decision Tree Simplification (SDM 2012)
Incorporating Boosted Regression Trees into Ecological Latent Variable Models (AAAI 2011)
Syntactic Decision Tree LMs: Random Selection or Intelligent Design (EMNLP 2011)
Decision Tree Fields (ICCV 2011)
Confidence in Predictions from Random Tree Ensembles (ICDM 2011)
Speeding-Up Hoeffding-Based Regression Trees With Options (ICML 2011)
Density Estimation Trees (KDD 2011)
Bagging Gradient-Boosted Trees for High Precision, Low Variance Ranking Models (SIGIR 2011)
On the Complexity of Decision Making in Possibilistic Decision Trees (UAI 2011)
Adaptive Bootstrapping of Recommender Systems Using Decision Trees (WSDM 2011)
Parallel Boosted Regression Trees for Web Search Ranking (WWW 2011)
Discrimination Aware Decision Tree Learning (ICDM 2010)
Decision Trees for Uplift Modeling (ICDM 2010)
Learning Markov Network Structure with Decision Trees (ICDM 2010)
Multivariate Dyadic Regression Trees for Sparse Learning Problems (NIPS 2010)
Fast and Accurate Gene Prediction by Decision Tree Classification (SDM 2010)
A Robust Decision Tree Algorithm for Imbalanced Data Sets (SDM 2010)
Stochastic Gradient Boosted Distributed Decision Trees (CIKM 2009)
Feature Selection for Ranking Using Boosted Trees (CIKM 2009)
Thai Word Segmentation with Hidden Markov Model and Decision Tree (PAKDD 2009)
Parameter Estimdation in Semi-Random Decision Tree Ensembling on Streaming Data (PAKDD 2009)
DTU: A Decision Tree for Uncertain Data (PAKDD 2009)
Predicting Future Decision Trees from Evolving Data (ICDM 2008)
Bayes Optimal Classification for Decision Trees (ICML 2008)
A New Credit Scoring Method Based on Rough Sets and Decision Tree (PAKDD 2008)
A Comparison of Different Off-Centered Entropies to Deal with Class Imbalance for Decision Trees (PAKDD 2008)
BOAI: Fast Alternating Decision Tree Induction Based on Bottom-Up Evaluation (PAKDD 2008)
A General Framework for Estimating Similarity of Datasets and Decision Trees: Exploring Semantic Similarity of Decision Trees (SDM 2008)
ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data (SDM 2008)
Tree-based Classifiers for Bilayer Video Segmentation (CVPR 2007)
Additive Groves of Regression Trees (ECML 2007)
Decision Tree Instability and Active Learning (ECML 2007)
Ensembles of Multi-Objective Decision Trees (ECML 2007)
Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble (ECML 2007)
Sample Compression Bounds for Decision Trees (ICML 2007)
A Tighter Error Bound for Decision Tree Learning Using PAC Learnability (IJCAI 2007)
Keep the Decision Tree and Estimate the Class Probabilities Using its Decision Boundary (IJCAI 2007)
Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree (IJCAI 2007)
Scalable Look-ahead Linear Regression Trees (KDD 2007)
Mining Optimal Decision Trees from Itemset Lattices (KDD 2007)
A Hybrid Multi-group Privacy-Preserving Approach for Building Decision Trees (PAKDD 2007)
Decision Tree Methods for Finding Reusable MDP Homomorphisms (AAAI 2006)
A Fast Decision Tree Learning Algorithm (AAAI 2006)
Anytime Induction of Decision Trees: An Iterative Improvement Approach (AAAI 2006)
When a Decision Tree Learner Has Plenty of Time (AAAI 2006)
Decision Trees for Functional Variables (ICDM 2006)
Cost-Sensitive Decision Tree Learning for Forensic Classification (ECML 2006)
Improving the Ranking Performance of Decision Trees (ECML 2006)
A General Framework for Accurate and Fast Regression by Data Summarization in Random Decision Trees (KDD 2006)
Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction (PAKDD 2006)
Variable Randomness in Decision Tree Ensembles (PAKDD 2006)
Generalized Conditional Entropy and a Metric Splitting Criterion for Decision Trees (PAKDD 2006)
Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics (PKDD 2006)
k-Anonymous Decision Tree Induction (PKDD 2006)
Representing Conditional Independence Using Decision Trees (AAAI 2005)
Use of Expert Knowledge for Decision Tree Pruning (AAAI 2005)
Model Selection in Omnivariate Decision Trees (ECML 2005)
Combining Bias and Variance Reduction Techniques for Regression Trees (ECML 2005)
Simple Test Strategies for Cost-Sensitive Decision Trees (ECML 2005)
Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree Approaches (ICDM 2005)
Exploiting Informative Priors for Bayesian Classification and Regression Trees (IJCAI 2005)
Ranking Cases with Decision Trees: a Geometric Method that Preserves Intelligibility (IJCAI 2005)
Maximizing Tree Diversity by Building Complete-Random Decision Trees (PAKDD 2005)
Hybrid Cost-Sensitive Decision Tree (PKDD 2005)
Tree2 - Decision Trees for Tree Structured Data (PKDD 2005)
Building Decision Trees on Records Linked through Key References (SDM 2005)
Decision Tree Induction in High Dimensional, Hierarchically Distributed Databases (SDM 2005)
Boosted Decision Trees for Word Recognition in Handwritten Document Retrieval (SIGIR 2005)
On the Optimality of Probability Estimation by Random Decision Trees (AAAI 2004)
Occam's Razor and a Non-Syntactic Measure of Decision Tree Complexity (AAAI 2004)
Using Emerging Patterns and Decision Trees in Rare-Class Classification (ICDM 2004)
Orthogonal Decision Trees (ICDM 2004)
Improving the Reliability of Decision Tree and Naive Bayes Learners (ICDM 2004)
Communication Efficient Construction of Decision Trees Over Heterogeneously Distributed Data (ICDM 2004)
Decision Tree Evolution Using Limited Number of Labeled Data Items from Drifting Data Streams (ICDM 2004)
Lookahead-based Algorithms for Anytime Induction of Decision Trees (ICML 2004)
Decision Trees with Minimal Costs (ICML 2004)
Training Conditional Random Fields via Gradient Tree Boosting (ICML 2004)
Detecting Structural Metadata with Decision Trees and Transformation-Based Learning (NAACL 2004)
On the Adaptive Properties of Decision Trees (NIPS 2004)
A Metric Approach to Building Decision Trees Based on Goodman-Kruskal Association Index (PAKDD 2004)
Rademacher Penalization over Decision Tree Prunings (ECML 2003)
Ensembles of Cascading Trees (ICDM 2003)
Postprocessing Decision Trees to Extract Actionable Knowledge (ICDM 2003)
K-D Decision Tree: An Accelerated and Memory Efficient Nearest Neighbor Classifier (ICDM 2003)
Identifying Markov Blankets with Decision Tree Induction (ICDM 2003)
Comparing Naive Bayes, Decision Trees, and SVM with AUC and Accuracy (ICDM 2003)
Boosting Lazy Decision Trees (ICML 2003)
Decision Tree with Better Ranking (ICML 2003)
Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction (IJCAI 2003)
Efficient Decision Tree Construction on Streaming Data (KDD 2003)
PaintingClass: Interactive Construction Visualization and Exploration of Decision Trees (KDD 2003)
Accurate Decision Trees for Mining High-Speed Data Streams (KDD 2003)
Near-Minimax Optimal Classification with Dyadic Classification Trees (NIPS 2003)
Improving Performance of Decision Tree Algorithms with Multi-edited Nearest Neighbor Rule (PAKDD 2003)
Arbogodai: a New Approach for Decision Trees (PKDD 2003)
Communication and Memory Efficient Parallel Decision Tree Construction (SDM 2003)
Decision Tree Classification of Spatial Data Patterns from Videokeratography using Zernicke Polynomials (SDM 2003)
Multiclass Alternating Decision Trees (ECML 2002)
Heterogeneous Forests of Decision Trees (ICANN 2002)
Solving the Fragmentation Problem of Decision Trees by Discovering Boundary Emerging Patterns (ICDM 2002)
Solving the Fragmentation Problem of Decision Trees by Discovering Boundary Emerging Patterns (ICDM 2002)
Learning Decision Trees Using the Area Under the ROC Curve (ICML 2002)
Finding an Optimal Gain-Ratio Subset-Split Test for a Set-Valued Attribute in Decision Tree Induction (ICML 2002)
Efficiently Mining Frequent Trees in a Forest (KDD 2002)
SECRET: a Scalable Linear Regression Tree Algorithm (KDD 2002)
Instability of Decision Tree Classification Algorithms (KDD 2002)
Extracting Decision Trees From Trained Neural Networks (KDD 2002)
Dyadic Classification Trees via Structural Risk Minimization (NIPS 2002)
Approximate Splitting for Ensembles of Trees using Histograms (SDM 2002)
Japanese Named Entity Recognition based on a Simple Rule Generator and Decision Tree Learning (ACL 2001)
Message Length as an Effective Ockham's Razor in Decision Tree Induction (AISTATS 2001)
SQL Database Primitives for Decision Tree Classifiers (CIKM 2001)
A Unified Framework for Evaluation Metrics in Classification Using Decision Trees (ECML 2001)
Backpropagation in Decision Trees for Regression (ECML 2001)
Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reduction (ECML 2001)
Mining Decision Trees from Data Streams in a Mobile Environment (ICDM 2001)
Efficient Determination of Dynamic Split Points in a Decision Tree (ICDM 2001)
A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods (ICDM 2001)
Efficient Algorithms for Decision Tree Cross-Validation (ICML 2001)
Bias Correction in Classification Tree Construction (ICML 2001)
Breeding Decision Trees Using Evolutionary Techniques (ICML 2001)
Obtaining Calibrated Probability Estimates from Decision Trees and Naive Bayesian Classifiers (ICML 2001)
Temporal Decision Trees or the lazy ECU vindicated (IJCAI 2001)
Data Mining Criteria for Tree-based Regression and Classification (KDD 2001)
A Decision Tree of Bigrams is an Accurate Predictor of Word Sense (NAACL 2001)
Rule Reduction over Numerical Attributes in Decision Tree Using Multilayer Perceptron (PAKDD 2001)
A Scalable Algorithm for Rule Post-pruning of Large Decision Trees (PAKDD 2001)
Optimizing the Induction of Alternating Decision Trees (PAKDD 2001)
Interactive Construction of Decision Trees (PAKDD 2001)
Bloomy Decision Tree for Multi-objective Classification (PKDD 2001)
A Fourier Analysis Based Approach to Learning Decision Trees in a Distributed Environment (SDM 2001)
Intuitive Representation of Decision Trees Using General Rules and Exceptions (AAAI 2000)
Tagging Unknown Proper Names Using Decision Trees (ACL 2000)
Clustering Through Decision Tree Construction (CIKM 2000)
Handling Continuous-Valued Attributes in Decision Tree with Neural Network Modelling (ECML 2000)
Investigation and Reduction of Discretization Variance in Decision Tree Induction (ECML 2000)
Nonparametric Regularization of Decision Trees (ECML 2000)
Exploiting the Cost (In)sensitivity of Decision Tree Splitting Criteria (ICML 2000)
Multi-agent Q-learning and Regression Trees for Automated Pricing Decisions (ICML 2000)
Growing Decision Trees on Support-less Association Rules (KDD 2000)
Efficient Algorithms for Constructing Decision Trees with Constraints (KDD 2000)
Interactive Visualization in Mining Large Decision Trees (PAKDD 2000)
VQTree: Vector Quantization for Decision Tree Induction (PAKDD 2000)
Some Enhencements of Decision Tree Bagging (PKDD 2000)
Combining Multiple Models with Meta Decision Trees (PKDD 2000)
Induction of Multivariate Decision Trees by Using Dipolar Criteria (PKDD 2000)
Decision Tree Toolkit: A Component-Based Library of Decision Tree Algorithms (PKDD 2000)
Modeling Decision Tree Performance with the Power Law (AISTATS 1999)
Causal Mechanisms and Classification Trees for Predicting Chemical Carcinogens (AISTATS 1999)
POS Tags and Decision Trees for Language Modeling (EMNLP 1999)
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees (ICML 1999)
The Alternating Decision Tree Learning Algorithm (ICML 1999)
Boosting with Multi-Way Branching in Decision Trees (NIPS 1999)
Learning Sorting and Decision Trees with POMDPs (ICML 1998)
Using a Permutation Test for Attribute Selection in Decision Trees (ICML 1998)
A Fast and Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization (ICML 1998)
Pessimistic Decision Tree Pruning Based Continuous-Time (ICML 1997)
PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction (ICML 1997)
Option Decision Trees with Majority Votes (ICML 1997)
Integrating Feature Construction with Multiple Classifiers in Decision Tree Induction (ICML 1997)
Functional Models for Regression Tree Leaves (ICML 1997)
The Effects of Training Set Size on Decision Tree Complexity (ICML 1997)
Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis (NIPS 1997)
Data-Dependent Structural Risk Minimization for Perceptron Decision Trees (NIPS 1997)
Generalization in Decision Trees and DNF: Does Size Matter (NIPS 1997)
Second Tier for Decision Trees (ICML 1996)
Non-Linear Decision Trees - NDT (ICML 1996)
Learning Relational Concepts with Decision Trees (ICML 1996)
A Hill-Climbing Approach for Optimizing Classification Trees (AISTATS 1995)
An Exact Probability Metric for Decision Tree Splitting (AISTATS 1995)
On Pruning and Averaging Decision Trees (ICML 1995)
On Handling Tree-Structured Attributed in Decision Tree Learning (ICML 1995)
Retrofitting Decision Tree Classifiers Using Kernel Density Estimation (ICML 1995)
Increasing the Performance and Consistency of Classification Trees by Using the Accuracy Criterion at the Leaves (ICML 1995)
Efficient Algorithms for Finding Multi-way Splits for Decision Trees (ICML 1995)
Theory and Applications of Agnostic PAC-Learning with Small Decision Trees (ICML 1995)
Boosting Decision Trees (NIPS 1995)
Using Pairs of Data-Points to Define Splits for Decision Trees (NIPS 1995)
A New Pruning Method for Solving Decision Trees and Game Trees (UAI 1995)
A Statistical Approach to Decision Tree Modeling (ICML 1994)
In Defense of C4.5: Notes Learning One-Level Decision Trees (ICML 1994)
An Improved Algorithm for Incremental Induction of Decision Trees (ICML 1994)
Decision Tree Parsing using a Hidden Derivation Model (NAACL 1994)
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