SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 951–975 of 1706 papers

TitleStatusHype
Enhancing Generalizability of Predictive Models with Synergy of Data and Physics—0
Enhancing IoT Security: A Novel Feature Engineering Approach for ML-Based Intrusion Detection Systems—0
Enhancing Molecular Design through Graph-based Topological Reinforcement Learning—0
Enhancing Physics-Informed Neural Networks Through Feature Engineering—0
Enhancing Tabular Data Optimization with a Flexible Graph-based Reinforced Exploration Strategy—0
Enhancing Wind Speed and Wind Power Forecasting Using Shape-Wise Feature Engineering: A Novel Approach for Improved Accuracy and Robustness—0
Enriching Tabular Data with Contextual LLM Embeddings: A Comprehensive Ablation Study for Ensemble Classifiers—0
Ensemble learning of diffractive optical networks—0
Ensemble Learning to Assess Dynamics of Affective Experience Ratings and Physiological Change—0
ERNIE at SemEval-2020 Task 10: Learning Word Emphasis Selection by Pre-trained Language Model—0
Escalation Prediction using Feature Engineering: Addressing Support Ticket Escalations within IBM's Ecosystem—0
EssayJudge: A Multi-Granular Benchmark for Assessing Automated Essay Scoring Capabilities of Multimodal Large Language Models—0
Estimating Brain Age with Global and Local Dependencies—0
Estimation of mitral valve hinge point coordinates -- deep neural net for echocardiogram segmentation—0
eTOP: Early Termination of Pipelines for Faster Training of AutoML Systems—0
Event Argument Identification on Dependency Graphs with Bidirectional LSTMs—0
Event Extraction with Generative Adversarial Imitation Learning—0
Event Nugget Detection with Forward-Backward Recurrent Neural Networks—0
Everybody likes short sentences - A Data Analysis for the Text Complexity DE Challenge 2022—0
EviNets: Neural Networks for Combining Evidence Signals for Factoid Question Answering—0
Expected F-Measure Training for Shift-Reduce Parsing with Recurrent Neural Networks—0
Explainable Adversarial Learning Framework on Physical Layer Secret Keys Combating Malicious Reconfigurable Intelligent Surface—0
Explainable AI Integrated Feature Engineering for Wildfire Prediction—0
Explainable Automatic Grading with Neural Additive Models—0
Explainable cognitive decline detection in free dialogues with a Machine Learning approach based on pre-trained Large Language Models—0
Show:102550
← PrevPage 39 of 69Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified