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Data pre-processing

Known as: Data preprocessing 
Data pre-processing is an important step in the data mining process. The phrase "garbage in, garbage out" is particularly applicable to data mining… Expand
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Related topics

Related topics

6 relations
Data miningData qualityFeature extractionFeature selection
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Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
Transforming big data into smart data: An insight on the use of the k‐nearest neighbors algorithm to obtain quality data
The k‐nearest neighbors algorithm is characterized as a simple yet effective data mining technique. The main drawback of this… Expand
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Highly Cited
2015
Highly Cited
2015
Efficient and Robust Automated Machine Learning
The success of machine learning in a broad range of applications has led to an ever-growing demand for machine learning systems… Expand
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Highly Cited
2012
Highly Cited
2012
Multi-column deep neural networks for image classification
Traditional methods of computer vision and machine learning cannot match human performance on tasks such as the recognition of… Expand
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Highly Cited
2004
Highly Cited
2004
Machine Learning for the Detection of Oil Spills in Satellite Radar Images
During a project examining the use of machine learning techniques for oil spill detection, we encountered several essential… Expand
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Highly Cited
2004
Highly Cited
2004
Discovering Knowledge in Data: An Introduction to Data Mining
The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications… Expand
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Highly Cited
2002
Highly Cited
2002
Precomputed radiance transfer for real-time rendering in dynamic, low-frequency lighting environments
We present a new, real-time method for rendering diffuse and glossy objects in low-frequency lighting environments that captures… Expand
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Highly Cited
2000
Highly Cited
2000
Random Data Analysis and Measurement Procedures
This is a new edition of a book on random data analysis which has been on the market since 1966 and which was extensively revised… Expand
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Highly Cited
2000
Highly Cited
2000
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the… Expand
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Highly Cited
1999
Highly Cited
1999
Data mining: practical machine learning tools and techniques, 3rd Edition
Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as… Expand
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Highly Cited
1997
Highly Cited
1997
Wrappers for Feature Subset Selection
Abstract In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset… Expand
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