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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

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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.
2019
2019
Using Convolutional Neural Networks for Sentiment Attitude Extraction from Analytical Texts
In this paper we present an application of the specific neural network model for sentiment attitude extraction without… 
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… 
2018
2018
Classification of Hanging Garments Using Learned Features Extracted from 3D Point Clouds
The presented work deals with classification of garment categories including pants, shorts, shirts, T-shirts and towels. The… 
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… 
Review
2017
Review
2017
Credible user-review incorporated collaborative filtering for video recommendation system
A system that recommends an item to a user that he/she is likely to be interested in is said to be a recommender system… 
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
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
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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