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Feature engineering

Feature engineering is the process of using domain knowledge of the data to create features that make machine learning algorithms work. Feature… 
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Related topics

Related topics

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Constrained conditional modelDeep feature synthesisDeep learningFeature (machine learning)

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
NILC at CWI 2018: Exploring Feature Engineering and Feature Learning
This paper describes the results of NILC team at CWI 2018. We developed solutions following three approaches: (i) a feature… 
2017
2017
VeNICE: A very deep neural network approach to no-reference image assessment
Image Quality Assessment (IQA) remains a complex and challenging problem that has garnered great interest by the research… 
2016
2016
Gender recognition from face images with trainable COSFIRE filters
Gender recognition from face images is an important application in the fields of security, retail advertising and marketing. We… 
2016
2016
Sentiment analysis via integrating distributed representations of variable-length word sequence
2016
2016
Course Learning Outcome Performance Improvement: A Remedial Action Classification Based Approach
Continuous Improvement is an essential element in any quality or accreditation process within academia or even industry. To… 
2016
2016
Deep learning based human behavior recognition in industrial workflows
We consider the fully automated behavior understanding through visual cues in industrial environments. In contrast to most… 
2016
2016
Offline Arabic Handwritten recognition system with dropout applied in Deep networks based-SVMs
As a machine learning algorithms, deep learning algorithms developed in recent years, have been successfully practiced in many… 
2015
2015
Localized Deep Extreme Learning Machines for Efficient RGB-D Object Recognition
Existing RGB-D object recognition methods either use channel specific handcrafted features, or learn features with deep networks… 
2015
2015
A Re-ranking Model for Dependency Parser with Recursive Convolutional Neural Network
In this work, we address the problem to model all the nodes (words or phrases) in a dependency tree with the dense… 
Highly Cited
2011
Highly Cited
2011
Shallow Discourse Parsing with Conditional Random Fields
Parsing discourse is a challenging natural language processing task. In this paper we take a data driven approach to identify… 
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