A few useful things to know about machine learning
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Citation edge evidence
- Deep learning applications and challenges in big data analytics→A few useful things to know about machine learningLegacy edge — source detail unavailable
- Deep Learning for Health Informatics→A few useful things to know about machine learningLegacy edge — source detail unavailable
- [No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]→A few useful things to know about machine learningLegacy edge — source detail unavailable
- Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health R…→A few useful things to know about machine learningLegacy edge — source detail unavailable
- A few useful things to know about machine learning→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
- A few useful things to know about machine learning→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- A few useful things to know about machine learning→CausalityLegacy edge — source detail unavailable
- A few useful things to know about machine learning→Learning Deep Architectures for AILegacy edge — source detail unavailable
- A few useful things to know about machine learning→Learning Deep Architectures for AILegacy edge — source detail unavailable
- A few useful things to know about machine learning→Causality: Models, Reasoning and InferenceLegacy edge — source detail unavailable
- A few useful things to know about machine learning→On the Optimality of the Simple Bayesian Classifier under Zero-One LossLegacy edge — source detail unavailable
- A few useful things to know about machine learning→Causality: models, reasoning, and inferenceLegacy edge — source detail unavailable
- A few useful things to know about machine learning→Markov logic networksLegacy edge — source detail unavailable
- A few useful things to know about machine learning→An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…Legacy edge — source detail unavailable
- A few useful things to know about machine learning→Bayesian TheoryLegacy edge — source detail unavailable
- A few useful things to know about machine learning→The Lack of A Priori Distinctions Between Learning AlgorithmsLegacy edge — source detail unavailable
- Markov logic networks→On the Optimality of the Simple Bayesian Classifier under Zero-One LossLegacy edge — source detail unavailable
- Learning Deep Architectures for AI→The Nature of Statistical Learning TheoryLegacy edge — source detail unavailable
- Deep learning applications and challenges in big data analytics→Learning Deep Architectures for AILegacy edge — source detail unavailable
- On the Optimality of the Simple Bayesian Classifier under Zero-One Loss→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→C4.5: Programs for Machine LearningLegacy edge — source detail unavailable
- An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→On the Optimality of the Simple Bayesian Classifier under Zero-One LossLegacy edge — source detail unavailable
- An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia…→Bayesian TheoryLegacy edge — source detail unavailable
- Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health R…→Deep Learning for Health InformaticsLegacy edge — source detail unavailable
- [No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]→The Lack of A Priori Distinctions Between Learning AlgorithmsLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| The Nature of Statistical Learning Theory | 1995 | 39,409 |
| C4.5: Programs for Machine Learning | 1992 | 23,704 |
| Causality | 2009 | 11,477 |
| Learning Deep Architectures for AI | 2009 | 6,951 |
| Learning Deep Architectures for AI | 2009 | 5,077 |
| Causality: Models, Reasoning and Inference | 2001 | 4,831 |
| On the Optimality of the Simple Bayesian Classifier under Zero-One Loss | 1997 | 3,099 |
| Causality: models, reasoning, and inference | 2000 | 2,920 |
| Markov logic networks | 2006 | 2,684 |
| An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Varia… | 1999 | 2,656 |
| Bayesian Theory | 1994 | 2,168 |
| The Lack of A Priori Distinctions Between Learning Algorithms | 1996 | 1,661 |
What cites it, inside the corpus
Links
Topics
| Machine Learning and Data Classification | Computer Science |
| Bayesian Modeling and Causal Inference | Computer Science |
| Machine Learning and Algorithms | Computer Science |
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complete
Nothing in this record contradicts itself and no field we check is missing.
- supports1 author record(s) attached.
- supports31 reference(s) recorded.
- neutralThe DOI carries no year to check against.
- supportsA title is present.
Provenance
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