Fast Effective Rule Induction
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Citation edge evidence
- SMOTE: Synthetic Minority Over-sampling Technique→Fast Effective Rule InductionLegacy edge — source detail unavailable
- Experiments with a new boosting algorithm→Fast Effective Rule InductionLegacy edge — source detail unavailable
- Supervised Machine Learning: A Review of Classification Techniques→Fast Effective Rule InductionLegacy edge — source detail unavailable
- A Survey of Outlier Detection Methodologies→Fast Effective Rule InductionLegacy edge — source detail unavailable
- A Short Introduction to Boosting→Fast Effective Rule InductionLegacy edge — source detail unavailable
- BoosTexter: A Boosting-based System for Text Categorization→Fast Effective Rule InductionLegacy edge — source detail unavailable
- The Boosting Approach to Machine Learning: An Overview→Fast Effective Rule InductionLegacy edge — source detail unavailable
- RUSBoost: A Hybrid Approach to Alleviating Class Imbalance→Fast Effective Rule InductionLegacy edge — source detail unavailable
- SMOTEBoost: Improving Prediction of the Minority Class in Boosting→Fast Effective Rule InductionLegacy edge — source detail unavailable
- Transfer Learning for Reinforcement Learning Domains: A Survey→Fast Effective Rule InductionLegacy edge — source detail unavailable
- Machine learning: a review of classification and combining techniques→Fast Effective Rule InductionLegacy edge — source detail unavailable
- Support vector machines for spam categorization→Fast Effective Rule InductionLegacy edge — source detail unavailable
- Sentiment strength detection in short informal text→Fast Effective Rule InductionLegacy edge — source detail unavailable
- Mining with rarity→Fast Effective Rule InductionLegacy edge — source detail unavailable
- Fast Effective Rule Induction→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- SMOTEBoost: Improving Prediction of the Minority Class in Boosting→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
- SMOTEBoost: Improving Prediction of the Minority Class in Boosting→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- SMOTEBoost: Improving Prediction of the Minority Class in Boosting→SMOTE: Synthetic Minority Over-sampling TechniqueLegacy edge — source detail unavailable
- Supervised Machine Learning: A Review of Classification Techniques→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- Supervised Machine Learning: A Review of Classification Techniques→A Survey of Outlier Detection MethodologiesLegacy edge — source detail unavailable
- Mining with rarity→SMOTEBoost: Improving Prediction of the Minority Class in BoostingLegacy edge — source detail unavailable
- Mining with rarity→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- Mining with rarity→SMOTE: Synthetic Minority Over-sampling TechniqueLegacy edge — source detail unavailable
- BoosTexter: A Boosting-based System for Text Categorization→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
- Machine learning: a review of classification and combining techniques→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- Machine learning: a review of classification and combining techniques→A Survey of Outlier Detection MethodologiesLegacy edge — source detail unavailable
- RUSBoost: A Hybrid Approach to Alleviating Class Imbalance→SMOTEBoost: Improving Prediction of the Minority Class in BoostingLegacy edge — source detail unavailable
- RUSBoost: A Hybrid Approach to Alleviating Class Imbalance→Mining with rarityLegacy edge — source detail unavailable
- RUSBoost: A Hybrid Approach to Alleviating Class Imbalance→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
- RUSBoost: A Hybrid Approach to Alleviating Class Imbalance→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- RUSBoost: A Hybrid Approach to Alleviating Class Imbalance→A Short Introduction to BoostingLegacy edge — source detail unavailable
- RUSBoost: A Hybrid Approach to Alleviating Class Imbalance→SMOTE: Synthetic Minority Over-sampling TechniqueLegacy edge — source detail unavailable
- Experiments with a new boosting algorithm→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- A Survey of Outlier Detection Methodologies→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- A Short Introduction to Boosting→BoosTexter: A Boosting-based System for Text CategorizationLegacy edge — source detail unavailable
- A Short Introduction to Boosting→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
- A Short Introduction to Boosting→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- SMOTE: Synthetic Minority Over-sampling Technique→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- The Boosting Approach to Machine Learning: An Overview→BoosTexter: A Boosting-based System for Text CategorizationLegacy edge — source detail unavailable
- The Boosting Approach to Machine Learning: An Overview→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
- The Boosting Approach to Machine Learning: An Overview→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- Support vector machines for spam categorization→Experiments with a new boosting algorithmLegacy edge — source detail unavailable
- Support vector machines for spam categorization→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- Sentiment strength detection in short informal text→BoosTexter: A Boosting-based System for Text CategorizationLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| C4.5: Programs for Machine Learning | 1992 | 23,704 |
What cites it, inside the corpus
Links
Topics
| Machine Learning and Data Classification | Computer Science |
| Machine Learning and Algorithms | Computer Science |
| Imbalanced Data Classification Techniques | Computer Science |
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- supports1 author record(s) attached.
- supports19 reference(s) recorded.
- neutralThe DOI carries no year to check against.
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