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 301–325 of 1706 papers

TitleStatusHype
A Gated Recurrent Unit Approach to Bitcoin Price Prediction—0
Parkinson's Disease Recognition Using SPECT Image and Interpretable AI: A Tutorial—0
Challenges and recommendations for Electronic Health Records data extraction and preparation for dynamic prediction modelling in hospitalized patients -- a practical guide—0
A framework for mining lifestyle profiles through multi-dimensional and high-order mobility feature clustering—0
A novel Network Science Algorithm for Improving Triage of Patients—0
A novel deep learning-based approach for sleep apnea detection using single-lead ECG signals—0
A Framework for Empowering Reinforcement Learning Agents with Causal Analysis: Enhancing Automated Cryptocurrency Trading—0
A Data-Driven Method for Recognizing Automated Negotiation Strategies—0
A non-DNN Feature Engineering Approach to Dependency Parsing -- FBAML at CoNLL 2017 Shared Task—0
A Food Recommender System in Academic Environments Based on Machine Learning Models—0
A Data-driven Deep Learning Approach for Bitcoin Price Forecasting—0
BertAA : BERT fine-tuning for Authorship Attribution—0
Benchmark Performance of Machine And Deep Learning Based Methodologies for Urdu Text Document Classification—0
A Flexible and Easy-to-use Semantic Role Labeling Framework for Different Languages—0
Capturing ``attrition intensifying'' structural traits from didactic interaction sequences of MOOC learners—0
Dynamic Bayesian Networks for Predicting Cryptocurrency Price Directions: Uncovering Causal Relationships—0
Character-Aware Neural Networks for Arabic Named Entity Recognition for Social Media—0
Chemellia: An Ecosystem for Atomistic Scientific Machine Learning—0
Benchmarking Time Series Forecasting Models: From Statistical Techniques to Foundation Models in Real-World Applications—0
Affect inTweets: A Transfer Learning Approach—0
Benchmarking Graph Neural Networks for Document Layout Analysis in Public Affairs—0
BERTMap: A BERT-based Ontology Alignment System—0
Better Model Selection with a new Definition of Feature Importance—0
Beyond Context: A New Perspective for Word Embeddings—0
Behavioral Modeling for Churn Prediction: Early Indicators and Accurate Predictors of Custom Defection and Loyalty—0
Show:102550
← PrevPage 13 of 69Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified