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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 1051–1100 of 1706 papers

TitleStatusHype
Forecasting the 2017-2018 Yemen Cholera Outbreak with Machine Learning—0
Forensic Data Analytics for Anomaly Detection in Evolving Networks—0
Fourier Transform Approach to Machine Learning III: Fourier Classification—0
F-RBA: A Federated Learning-based Framework for Risk-based Authentication—0
Free-Text Keystroke Dynamics for User Authentication—0
From Data to Decisions: The Transformational Power of Machine Learning in Business Recommendations—0
From Digital Humanities to Quantum Humanities: Potentials and Applications—0
From Features to Transformers: Redefining Ranking for Scalable Impact—0
Gated Recursive and Sequential Deep Hierarchical Encoding for Detecting Incongruent News Articles—0
Gated Recursive Neural Network for Chinese Word Segmentation—0
GBD-NER at PARSEME Shared Task 2018: Multi-Word Expression Detection Using Bidirectional Long-Short-Term Memory Networks and Graph-Based Decoding—0
GCOF: Self-iterative Text Generation for Copywriting Using Large Language Model—0
Generalized Convolutional Neural Networks for Point Cloud Data—0
Generative Adversarial Networks Applied to Synthetic Financial Scenarios Generation—0
Generic Multi-modal Representation Learning for Network Traffic Analysis—0
Genre Separation Network with Adversarial Training for Cross-genre Relation Extraction—0
GenTAL: Generative Denoising Skip-gram Transformer for Unsupervised Binary Code Similarity Detection—0
GeoDecoder: Empowering Multimodal Map Understanding—0
Geomancer: An Open-Source Framework for Geospatial Feature Engineering—0
Geometric feature performance under downsampling for EEG classification tasks—0
Getting the Most out of AMR Parsing—0
GFS: Graph-based Feature Synthesis for Prediction over Relational Databases—0
Global Earth Magnetic Field Modeling and Forecasting with Spherical Harmonics Decomposition—0
Global Pose Estimation with an Attention-based Recurrent Network—0
Golden Reference-Free Hardware Trojan Localization using Graph Convolutional Network—0
GPT Assisted Annotation of Rhetorical and Linguistic Features for Interpretable Propaganda Technique Detection in News Text—0
GPTree: Towards Explainable Decision-Making via LLM-powered Decision Trees—0
Graph-based Dependency Parsing with Bidirectional LSTM—0
Graph Classification via Reference Distribution Learning: Theory and Practice—0
GraphCNNpred: A stock market indices prediction using a Graph based deep learning system—0
GraphGuard: Contrastive Self-Supervised Learning for Credit-Card Fraud Detection in Multi-Relational Dynamic Graphs—0
Graph Neural Networks and Boolean Satisfiability—0
Grasp-and-Lift Detection from EEG Signal Using Convolutional Neural Network—0
Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction—0
Growing Cosine Unit: A Novel Oscillatory Activation Function That Can Speedup Training and Reduce Parameters in Convolutional Neural Networks—0
GU-MLT-LT: Sentiment Analysis of Short Messages using Linguistic Features and Stochastic Gradient Descent—0
HARDCORE: H-field and power loss estimation for arbitrary waveforms with residual, dilated convolutional neural networks in ferrite cores—0
HAR-Net:Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition—0
HashCount at SemEval-2018 Task 3: Concatenative Featurization of Tweet and Hashtags for Irony Detection—0
Hashtag Recommendation with Topical Attention-Based LSTM—0
HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports—0
Helsinki-NLP at SemEval-2022 Task 2: A Feature-Based Approach to Multilingual Idiomaticity Detection—0
HeNet: A Deep Learning Approach on Intel^ Processor Trace for Effective Exploit Detection—0
Heterogeneous Information Network based Default Analysis on Banking Micro and Small Enterprise Users—0
Heuristic Feature Selection for Clickbait Detection—0
HiCat: A Semi-Supervised Approach for Cell Type Annotation—0
Hierarchical Low-Rank Tensors for Multilingual Transfer Parsing—0
Hierarchical neural model with attention mechanisms for the classification of social media text related to mental health—0
High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing—0
Highly Effective Arabic Diacritization using Sequence to Sequence Modeling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified