Induction of decision trees

Cited by (1,063)

Items 501–600 of 1,063

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22. Ordinal Regression by Extended Binary Classification
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23. Eliminating class noise in large datasets
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24. Data mining for providing a personalized learning path in creativity: An application of decision trees
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25. Data Mining Methods for Recommender Systems
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26. Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner
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29. Emotion Recognition From Multi-Channel EEG via Deep Forest
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33. A Novel Framework for Imputation of Missing Values in Databases
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37. PuDianNao
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38. Incremental Feature Selection
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43. Learning Trees an ules with Set-val ed Features
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47. Application of Machine Learning in Disease Prediction
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48. Error Reduction through Learning Multiple Descriptions
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49. Best-first Decision Tree Learning
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50. Learning preferences of new users in recommender systems
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51. Recent Advances in Trustworthy Explainable Artificial Intelligence: Status, Challenges, and Perspectives
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52. Unifying Instance-Based and Rule-Based Induction
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53. Making data visualization more efficient and effective: a survey
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54. Learning from Incomplete Data.
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55. Using Decision Trees to Improve Signature-Based Intrusion Detection
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56. Class-dependent discretization for inductive learning from continuous and mixed-mode data
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57. Stock market one-day ahead movement prediction using disparate data sources
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58. Multiple Comparisons in Induction Algorithms
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59. Automated text summarization and the SUMMARIST system
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60. A comparative assessment of classification methods
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61. Zero Shot Recognition with Unreliable Attributes
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62. A pattern recognition approach for software engineering data analysis
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63. Dynamics of Modeling in Data Mining: Interpretive Approach to Bankruptcy Prediction
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64. Computational intelligence methods for rule-based data understanding
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65. Decision trees: from efficient prediction to responsible AI
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66. Online big data-driven oil consumption forecasting with Google trends
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67. Development and Validation of a Learning Analytics Framework: Two Case Studies Using Support Vector Machines
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68. Advancements and Challenges in Machine Learning: A Comprehensive Review of Models, Libraries, Applications, and Algorithms
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69. A combined neural network and decision trees model for prognosis of breast cancer relapse
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70. Predicting recovery in patients suffering from traumatic brain injury by using admission variables and physiological data: a comparison between decision tree analysis and logistic regression
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71. The use of classification trees for bioinformatics
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72. Fuzzy decision trees by fuzzy ID3 algorithm and its application to diagnosis systems
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73. Assessment of supervised machine learning methods for fluid flows
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74. Self-paced Ensemble for Highly Imbalanced Massive Data Classification
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75. A systematic review of the prediction of hospital length of stay: Towards a unified framework
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76. Character Recognition Systems: A Guide for Students and Practitioners
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77. Feature Subset Selection by Bayesian network-based optimization
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78. Using assignment examples to infer weights for ELECTRE TRI method: Some experimental results
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79. Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?
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80. Invited review: Machine learning for materials developments in metals additive manufacturing
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81. Decision Tree and Ensemble Learning Algorithms with Their Applications in Bioinformatics
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82. Improving the impervious surface estimation with combined use of optical and SAR remote sensing images
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84. Extracting comprehensible models from trained neural networks
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86. A Novel Breast Tissue Density Classification Methodology
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87. Understanding Household Waste Separation Behaviour: Testing the Roles of Moral, Past Experience, and Perceived Policy Effectiveness within the Theory of Planned Behaviour
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88. A New Feature Transformation Method Based on Rotation for Speaker Identification
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89. CABARET: rule interpretation in a hybrid architecture
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90. Weight perturbation: an optimal architecture and learning technique for analog VLSI feedforward and recurrent multilayer networks
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91. Decision Trees for Uncertain Data
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92. DeepGini: prioritizing massive tests to enhance the robustness of deep neural networks
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93. Deep spatio-temporal graph convolutional network for traffic accident prediction
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94. Efficient sleep stage recognition system based on EEG signal using k-means clustering based feature weighting
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