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 501–525 of 1706 papers

TitleStatusHype
Deep Interaction Machine: A Simple but Effective Model for High-order Feature Interactions—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
Decoding and interpreting cortical signals with a compact convolutional neural network—0
A Survey on Data Collection for Machine Learning: a Big Data -- AI Integration Perspective—0
Deep Learning based, end-to-end metaphor detection in Greek language with Recurrent and Convolutional Neural Networks—0
Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory—0
Decision Tree Based Wrappers for Hearing Loss—0
A Survey on Data-Centric AI: Tabular Learning from Reinforcement Learning and Generative AI Perspective—0
Amrita_CEN at SemEval-2022 Task 6: A Machine Learning Approach for Detecting Intended Sarcasm using Oversampling—0
Deceptive Review Spam Detection via Exploiting Task Relatedness and Unlabeled Data—0
A Survey on Churn Analysis—0
DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison—0
A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends—0
Amrita_CEN at SemEval-2022 Task 4: Oversampling-based Machine Learning Approach for Detecting Patronizing and Condescending Language—0
Data Smashing 2.0: Sequence Likelihood (SL) Divergence For Fast Time Series Comparison—0
Dataset-Agnostic Recommender Systems—0
Dataiku's Solution to SPHERE's Activity Recognition Challenge—0
Data-driven Smart Ponzi Scheme Detection—0
Data-Driven Investigative Journalism For Connectas Dataset—0
Enhancing Sindhi Word Segmentation using Subword Representation Learning and Position-aware Self-attention—0
Data-driven intelligent computational design for products: Method, techniques, and applications—0
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective—0
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code—0
A Model of Coherence Based on Distributed Sentence Representation—0
Show:102550
← PrevPage 21 of 69Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified