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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 951–1000 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
Explainable Multi-class Classification of Medical Data—0
Explainable Neural Networks based on Additive Index Models—0
Explaining Classifiers Trained on Raw Hierarchical Multiple-Instance Data—0
Explaining Translationese: why are Neural Classifiers Better and what do they Learn?—0
Exploiting Meta-Cognitive Features for a Machine-Learning-Based One-Shot Group-Decision Aggregation—0
Exploiting Unsupervised Pre-training and Automated Feature Engineering for Low-resource Hate Speech Detection in Polish—0
Exploration of Proximity Heuristics in Length Normalization—0
Exploring Adversarial Examples in Malware Detection—0
Exploring Feature Importance and Explainability Towards Enhanced ML-Based DoS Detection in AI Systems—0
Exploring LLM Agents for Cleaning Tabular Machine Learning Datasets—0
Exploring Microstructural Dynamics in Cryptocurrency Limit Order Books: Better Inputs Matter More Than Stacking Another Hidden Layer—0
Exploring Patterns Behind Sports—0
Exploring Representations from Unlabeled Data with Co-training for Chinese Word Segmentation—0
Extended pipeline for content-based feature engineering in music genre recognition—0
Extracting Drug-Drug Interactions with Attention CNNs—0
Extracting Human Temporal Orientation from Facebook Language—0
Extracting PICO elements from RCT abstracts using 1-2gram analysis and multitask classification—0
Extraction of Heart Rate from PPG Signal: A Machine Learning Approach using Decision Tree Regression Algorithm—0
Extractive Text Summarization using Neural Networks—0
Fake News Detection using Stance Classification: A Survey—0
Fake News Early Detection: An Interdisciplinary Study—0
Fantastic Features and Where to Find Them: Detecting Cognitive Impairment with a Subsequence Classification Guided Approach—0
Fast and Accurate Decision Trees for Natural Language Processing Tasks—0
Fast and Accurate Performance Analysis of LTE Radio Access Networks—0
Fast and Accurate Reordering with ITG Transition RNN—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified