A few useful things to know about machine learning
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Summary
Tapping into the "folk knowledge" needed to advance machine learning applications is a natural next step in the development of artificial intelligence systems.
- Type
- article
- Published
- 2012-10-01
- Cited by
- 3,324
- References
- 28
- Access
- Open access
- OpenAlex
- https://openalex.org/W2161336914
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:2559675
Keywords
Computer science, Need to know, Artificial intelligence, Machine learning, Computer security
References
- Preventing "Overfitting" of Cross-Validation Data
- Big data: The next frontier for innovation, competition, and productivity
- Programs for Machine Learning
- A Unifeid Bias-Variance Decomposition and its Applications
- Bayesian Averaging of Classifiers and the Overfitting Problem
- The Role of Occam's Razor in Knowledge Discovery
- Markov logic networks
- Occam's razor
- Grammatically Biased Learning: Learning Logic Programs Using an Explicit Antecedent Description Language
- ON THE CONNECTION BETWEEN THE COMPLEXITY AND CREDIBILITY OF INFERRED MODELS
- Learning Deep Architectures for AI
- Mining complex models from arbitrarily large databases in constant time
- Controlling the false discovery rate: a practical and powerful approach to multiple testing
- C4.5: Programs for Machine Learning
- On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
- An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
- Machine learning as an experimental science
- Data Mining Practical Machine Learning Tools and Techniques
- Data mining
- Causality : Models , Reasoning , and Inference
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- Detecting Bacterial Vaginosis Using Machine Learning
- Advances and perspectives in computational prediction of microbial gene essentiality.
- Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
- Error rates reduction in handwritten digits classification using the MNIST data with Artificial Neural Networks
- Discriminant Processing In Multi-class Pattern Recognition Systems
- Intelligent Data Engineering and Automated Learning – IDEAL 2020: 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II
- Making tabletops useful with applications, frameworks and multi-tasking
- An efficient concept detection system via sparse ensemble learning
- Predicting Customer Churn at a Swedish CRM-system Company
- Correlating Gender Sensitivity and Learning Traits in Higher Education
- Ensemble methods in ordinal data classification
- Data Carving: Identifying and Removing Irrelevancies in the Data
- Machine learning approximation techniques using dual trees
- A LOCATION-AWARE SOCIAL MEDIA MONITORING SYSTEM
- An angle-based subspace anomaly detection approach to high-dimensional data: With an application to industrial fault detection
- Context classification for service robots
- A hybrid approach to inferring a consistent temporal relation set in natural language text
- Computational Advertising: Techniques for Targeting Relevant Ads
- Using Ontology-based Approaches to Representing Speech Transcripts for Automated Speech Scoring
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