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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
High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing—0
A Brief Survey of Machine Learning Methods for Emotion Prediction using Physiological Data—0
Gated Recursive and Sequential Deep Hierarchical Encoding for Detecting Incongruent News Articles—0
Investigating and Explaining Feature and Representation Learning in Translationese Classification—0
Reconstruction of Incomplete Wildfire Data using Deep Generative ModelsCode0
Quantifying yeast colony morphologies with feature engineering from time-lapse photographyCode0
EEG Based Emotion Sensing using convolutional neural networks—0
Supervised Learning based QoE Prediction of Video Streaming in Future Networks: A Tutorial with Comparative Study—0
AutoFITS: Automatic Feature Engineering for Irregular Time SeriesCode0
A Comprehensive Analytical Survey on Unsupervised and Semi-Supervised Graph Representation Learning Methods—0
Neural Architectures for Biological Inter-Sentence Relation Extraction—0
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective—0
Zero-shot hashtag segmentation for multilingual sentiment analysisCode1
Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review—0
BERTMap: A BERT-based Ontology Alignment System—0
Predicting Bandwidth Utilization on Network Links Using Machine Learning—0
Two-stage Deep Stacked Autoencoder with Shallow Learning for Network Intrusion Detection System—0
User-click Modelling for Predicting Purchase Intent—0
Transfer Learning in Conversational Analysis through Reusing Preprocessing Data as Supervisors—0
Team_BUDDI at ComMA@ICON: Exploring Individual and Joint Modelling Approaches for Detecting Aggression, Communal Bias and Gender Bias—0
BP-Net: Efficient Deep Learning for Continuous Arterial Blood Pressure Estimation using PhotoplethysmogramCode1
Dimensionality Reduction of Longitudinal 'Omics Data using Modern Tensor FactorizationCode1
On the combination of graph data for assessing thin-file borrowers' creditworthiness—0
A Deep Learning Approach for Macroscopic Energy Consumption Prediction with Microscopic Quality for Electric Vehicles—0
Understanding the Dynamics of DNNs Using Graph ModularityCode1
Interpreting Machine Learning Models for Room Temperature Prediction in Non-domestic BuildingsCode1
End-to-End Optimized Arrhythmia Detection Pipeline using Machine Learning for Ultra-Edge DevicesCode1
Precise Learning of Source Code Contextual Semantics via Hierarchical Dependence Structure and Graph Attention Networks—0
A Data-Centric Behavioral Machine Learning Platform to Reduce Health Inequalities—0
Innovative Measures of Patient and Disease Phenotyping: Optimizing Linguistic and Machine Learning Techniques in the Investigation of Electronic Health Record (EHR) Data—0
Automatic Analysis of Linguistic Features in Journal Articles of Different Academic Impacts with Feature Engineering Techniques—0
Automated PII Extraction from Social Media for Raising Privacy Awareness: A Deep Transfer Learning Approach—0
Artificial Intelligence Technology analysis using Artificial Intelligence patent through Deep Learning model and vector space model—0
Biologically Inspired Oscillating Activation Functions Can Bridge the Performance Gap between Biological and Artificial Neurons—0
Language Semantics Interpretation with an Interaction-based Recurrent Neural Networks—0
ICL’s Submission to the WMT21 Critical Error Detection Shared Task—0
A Hybrid Rule-Based and Neural Coreference Resolution System with an Evaluation on Dutch LiteratureCode1
Knowledge-driven Site Selection via Urban Knowledge Graph—0
Classification of fetal compromise during labour: signal processing and feature engineering of the cardiotocograph—0
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the BoundaryCode1
Concepts for Automated Machine Learning in Smart Grid Applications—0
Merging Two Cultures: Deep and Statistical Learning—0
Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature EngineeringCode0
Robust Event Classification Using Imperfect Real-world PMU Data—0
AEFE: Automatic Embedded Feature Engineering for Categorical Features—0
Structural Characterization for Dialogue DisentanglementCode1
Tutorial on Deep Learning for Human Activity RecognitionCode0
TEET! Tunisian Dataset for Toxic Speech Detection—0
Deep convolutional forest: a dynamic deep ensemble approach for spam detection in textCode0
Feature Imitating Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified