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Feature Engineering

Feature engineering is the process of taking a dataset and constructing explanatory variables — features — that can be used to train a machine learning model for a prediction problem. Often, data is spread across multiple tables and must be gathered into a single table with rows containing the observations and features in the columns.

The traditional approach to feature engineering is to build features one at a time using domain knowledge, a tedious, time-consuming, and error-prone process known as manual feature engineering. The code for manual feature engineering is problem-dependent and must be re-written for each new dataset.

Papers

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Showing 601–650 of 1706 papers

TitleStatusHype
Combining Lexical and Semantic-based Features for Answer Sentence Selection—0
Alejandro Mosquera at SemEval-2021 Task 1: Exploring Sentence and Word Features for Lexical Complexity Prediction—0
A Deep Learning Based Cost Model for Automatic Code Optimization—0
A Conditional Generative Model for Predicting Material Microstructures from Processing Methods—0
ABM: an automatic supervised feature engineering method for loss based models based on group and fused lasso—0
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT—0
Combination of Diverse Ranking Models for Personalized Expedia Hotel Searches—0
Argument Labeling of Explicit Discourse Relations using LSTM Neural Networks—0
Cognito: Automated Feature Engineering for Supervised Learning—0
A Review on Deep Learning Techniques Applied to Answer Selection—0
ALANIS at SemEval-2018 Task 3: A Feature Engineering Approach to Irony Detection in English Tweets—0
CoDet-M4: Detecting Machine-Generated Code in Multi-Lingual, Multi-Generator and Multi-Domain Settings—0
CodeForTheChange at SemEval-2019 Task 8: Skip-Thoughts for Fact Checking in Community Question Answering—0
A Review of Computational Approaches for Evaluation of Rehabilitation Exercises—0
A Language-Independent Neural Network for Event Detection—0
A Deep Learning Approach to Mapping Irrigation: IrrMapper-U-Net—0
CMUQ@Qatar:Using Rich Lexical Features for Sentiment Analysis on Twitter—0
CMUQ-Hybrid: Sentiment Classification By Feature Engineering and Parameter Tuning—0
A Recurrent and Compositional Model for Personality Trait Recognition from Short Texts—0
Clustering US Counties to Find Patterns Related to the COVID-19 Pandemic—0
CLULEX at SemEval-2021 Task 1: A Simple System Goes a Long Way—0
Are Accelerometers for Activity Recognition a Dead-end?—0
A Language-independent and Compositional Model for Personality Trait Recognition from Short Texts—0
CLIP-Motion: Learning Reward Functions for Robotic Actions Using Consecutive Observations—0
ArbDialectID at MADAR Shared Task 1: Language Modelling and Ensemble Learning for Fine Grained Arabic Dialect Identification—0
Clinical Text Classification with Rule-based Features and Knowledge-guided Convolutional Neural Networks—0
A Kernel Two-sample Test for Dynamical Systems—0
A Deep Learning Approach to Identify Rock Bolts in Complex 3D Point Clouds of Underground Mines Captured Using Mobile Laser Scanners—0
A Comprehensive Analytical Survey on Unsupervised and Semi-Supervised Graph Representation Learning Methods—0
Clinical Event Detection with Hybrid Neural Architecture—0
Clinical Document Classification Using Labeled and Unlabeled Data Across Hospitals—0
client2vec: Towards Systematic Baselines for Banking Applications—0
Clickbait detection using word embeddings—0
Arabic POS Tagging: Don't Abandon Feature Engineering Just Yet—0
A Joint Model for Chinese Microblog Sentiment Analysis—0
CLCL (Geneva) DINN Parser: a Neural Network Dependency Parser Ten Years Later—0
Arabic Named Entity Recognition: What Works and What's Next—0
Classifying single-qubit noise using machine learning—0
Classifying Semantic Clause Types: Modeling Context and Genre Characteristics with Recurrent Neural Networks and Attention—0
Arabic Diacritic Recovery Using a Feature-Rich biLSTM Model—0
AI WALKUP: A Computer-Vision Approach to Quantifying MDS-UPDRS in Parkinson's Disease—0
A Deep Learning Approach for Tweet Classification and Rescue Scheduling for Effective Disaster Management—0
Classifying Malware Using Function Representations in a Static Call Graph—0
A Progressive Transformer for Unifying Binary Code Embedding and Knowledge Transfer—0
Classification of residential and non-residential buildings based on satellite data using deep learning—0
A Process for the Evaluation of Node Embedding Methods in the Context of Node Classification—0
Classification of Operational Records in Aviation Using Deep Learning Approaches—0
Classification of fetal compromise during labour: signal processing and feature engineering of the cardiotocograph—0
Approximation Ratios of Graph Neural Networks for Combinatorial Problems—0
Classification of Electrical Impedance Tomography Data Using Machine Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified