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 426–450 of 1706 papers

TitleStatusHype
Morphological Profiling for Drug Discovery in the Era of Deep Learning—0
Unsupervised Multi-modal Feature Alignment for Time Series Representation Learning—0
Keyword spotting -- Detecting commands in speech using deep learning—0
GFS: Graph-based Feature Synthesis for Prediction over Relational Databases—0
Graph Coordinates and Conventional Neural Networks -- An Alternative for Graph Neural NetworksCode0
A framework for mining lifestyle profiles through multi-dimensional and high-order mobility feature clustering—0
LiDAR-based Outdoor Crowd Management for Smart Campus on the Edge—0
Introducing 3DCNN ResNets for ASD full-body kinematic assessment: a comparison with hand-crafted features—0
Neural Approximate Dynamic Programming for the Ultra-fast Order Dispatching Problem—0
Adaptive Modelling Approach for Row-Type Dependent Predictive Analysis (RTDPA): A Framework for Designing Machine Learning Models for Credit Risk Analysis in Banking Sector—0
Understanding learning from EEG data: Combining machine learning and feature engineering based on hidden Markov models and mixed modelsCode0
Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Tasks—0
Auto deep learning for bioacoustic signalsCode0
Classification of Various Types of Damages in Honeycomb Composite Sandwich Structures using Guided Wave Structural Health MonitoringCode0
IoT-Based Environmental Control System for Fish Farms with Sensor Integration and Machine Learning Decision Support—0
Leveraging sinusoidal representation networks to predict fMRI signals from EEG—0
CLIP-Motion: Learning Reward Functions for Robotic Actions Using Consecutive Observations—0
RELand: Risk Estimation of Landmines via Interpretable Invariant Risk MinimizationCode0
ReConTab: Regularized Contrastive Representation Learning for Tabular Data—0
A Data-driven Deep Learning Approach for Bitcoin Price Forecasting—0
Bi-Encoders based Species Normalization -- Pairwise Sentence Learning to Rank—0
Towards a Deep Learning-based Online Quality Prediction System for Welding Processes—0
Personalized human mobility prediction for HuMob challenge—0
A Framework for Empowering Reinforcement Learning Agents with Causal Analysis: Enhancing Automated Cryptocurrency Trading—0
A Novel Statistical Measure for Out-of-Distribution Detection in Data Quality Assurance—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified