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 1101–1125 of 1706 papers

TitleStatusHype
User Intent Prediction in Information-seeking ConversationsCode0
Recurrent Neural Networks for Time Series Forecasting—0
A Neural Network Based Explainable Recommender System—0
Weakly-Supervised Hierarchical Text ClassificationCode0
Feedforward Neural Network for Time Series Anomaly Detection—0
Designing Adversarially Resilient Classifiers using Resilient Feature Engineering—0
Can Deep Learning Predict Risky Retail Investors? A Case Study in Financial Risk Behavior Forecasting—0
A Hybrid Distribution Feeder Long-Term Load Forecasting Method Based on Sequence Prediction—0
An Unsupervised Approach for Aspect Category Detection Using Soft Cosine Similarity MeasureCode0
Time Series Featurization via Topological Data Analysis—0
Machine Learning for Wireless Link Quality Estimation: A Survey—0
Clinical Document Classification Using Labeled and Unlabeled Data Across Hospitals—0
AnyThreat: An Opportunistic Knowledge Discovery Approach to Insider Threat Detection—0
Customer Lifetime Value in Video Games Using Deep Learning and Parametric Models—0
Lagged correlation-based deep learning for directional trend change prediction in financial time series—0
Application of Clinical Concept Embeddings for Heart Failure Prediction in UK EHR data—0
Past, Present, and Future Approaches Using Computer Vision for Animal Re-Identification from Camera Trap Data—0
Robust cross-domain disfluency detection with pattern match networks—0
ML-Net: multi-label classification of biomedical texts with deep neural networksCode0
Cross-lingual Short-text Matching with Deep Learning—0
A Survey on Data Collection for Machine Learning: a Big Data -- AI Integration Perspective—0
Cuffless Blood Pressure Estimation from Electrocardiogram and Photoplethysmogram Using Waveform Based ANN-LSTM Network—0
Investigating context features hidden in End-to-End TTS—0
`Indicatements' that character language models learn English morpho-syntactic units and regularities—0
Spelling Error Correction Using a Nested RNN Model and Pseudo Training Data—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified