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

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Showing 126–150 of 1706 papers

TitleStatusHype
fseval: A Benchmarking Framework for Feature Selection and Feature Ranking AlgorithmsCode1
End-to-End Optimized Arrhythmia Detection Pipeline using Machine Learning for Ultra-Edge DevicesCode1
Graph Neural Networks for Quantifying Compatibility Mechanisms in Traditional Chinese MedicineCode1
Disentangled Attribution Curves for Interpreting Random Forests and Boosted TreesCode1
DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability DetectionCode1
Network Analytics for Anti-Money Laundering -- A Systematic Literature Review and Experimental EvaluationCode1
Anomaly Detection for Solder Joints Using β-VAECode1
Dual Attention U-Net with Feature Infusion: Pushing the Boundaries of Multiclass Defect SegmentationCode1
Efficient End-to-End AutoML via Scalable Search Space DecompositionCode1
Sequence-to-Sequence Learning with Latent Neural GrammarsCode1
Deep Voice: Real-time Neural Text-to-SpeechCode0
DeepTriangle: A Deep Learning Approach to Loss ReservingCode0
De-identification of Patient Notes with Recurrent Neural NetworksCode0
Activity2Vec: Learning ADL Embeddings from Sensor Data with a Sequence-to-Sequence ModelCode0
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural NetworksCode0
Deep Learning for Answer Sentence SelectionCode0
Deep Learning Chromatic and Clique Numbers of GraphsCode0
Deep Learning-Based Automatic Downbeat Tracking: A Brief ReviewCode0
Active DOP: A constituency treebank annotation tool with online learningCode0
Deep Learning-Based Noninvasive Screening of Type 2 Diabetes with Chest X-ray Images and Electronic Health RecordsCode0
deepQuest: A Framework for Neural-based Quality EstimationCode0
Descriptive Kernel Convolution Network with Improved Random Walk KernelCode0
Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait RecognitionCode0
A domain-agnostic approach for opinion prediction on speechCode0
DeepInf: Social Influence Prediction with Deep LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified