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
Compatible deep neural network framework with financial time series data, including data preprocessor, neural network model and trading strategyCode1
AutoML: A Survey of the State-of-the-ArtCode1
BP-Net: Efficient Deep Learning for Continuous Arterial Blood Pressure Estimation using PhotoplethysmogramCode1
AutoGL: A Library for Automated Graph LearningCode1
DeepFM: A Factorization-Machine based Neural Network for CTR PredictionCode1
AutoSmart: An Efficient and Automatic Machine Learning framework for Temporal Relational DataCode1
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the BoundaryCode1
Benchmarking Skeleton-based Motion Encoder Models for Clinical Applications: Estimating Parkinson's Disease Severity in Walking SequencesCode1
Benchmarks and Custom Package for Energy ForecastingCode1
Evaluation Toolkit For Robustness Testing Of Automatic Essay Scoring SystemsCode1
Analyzing Multispectral Satellite Imagery of South American Wildfires Using Deep Learning—0
Analysis of Rhythmic Phrasing: Feature Engineering vs. Representation Learning for Classifying Readout Poetry—0
Advancements in Tactile Hand Gesture Recognition for Enhanced Human-Machine Interaction—0
Machine Learning for Wireless Link Quality Estimation: A Survey—0
A multi-task learning model for malware classification with useful file access pattern from API call sequence—0
Advanced fraud detection using machine learning models: enhancing financial transaction security—0
Deep learning approach to control of prosthetic hands with electromyography signals—0
A Multitask Deep Learning Approach for User Depression Detection on Sina Weibo—0
A Multi-task Approach to Predict Likability of Books—0
A Dual-Layer Semantic Role Labeling System—0
A multi-model-based deep learning framework for short text multiclass classification with the imbalanced and extremely small data set—0
A Multi-Attention based Neural Network with External Knowledge for Story Ending Predicting Task—0
ADSAGE: Anomaly Detection in Sequences of Attributed Graph Edges applied to insider threat detection at fine-grained level—0
A Brief Survey of Machine Learning Methods for Emotion Prediction using Physiological Data—0
Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified