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 1301–1325 of 1706 papers

TitleStatusHype
Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly DetectionCode0
Spherical convolutions and their application in molecular modelling—0
OCR Post-Processing Text Correction using Simulated Annealing (OPTeCA)—0
Bingo at IJCNLP-2017 Task 4: Augmenting Data using Machine Translation for Cross-linguistic Customer Feedback Classification—0
Alibaba at IJCNLP-2017 Task 2: A Boosted Deep System for Dimensional Sentiment Analysis of Chinese Phrases—0
Stock Market Prediction with Deep Learning: A Character-based Neural Language Model for Event-based Trading—0
Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion—0
AutoLearn - Automated Feature Generation and SelectionCode0
Neurology-as-a-Service for the Developing World—0
SkipFlow: Incorporating Neural Coherence Features for End-to-End Automatic Text ScoringCode0
Convolutional Neural Network with Word Embeddings for Chinese Word SegmentationCode0
p-FP: Extraction, Classification, and Prediction of Website Fingerprints with Deep Learning—0
Event Argument Identification on Dependency Graphs with Bidirectional LSTMs—0
Chemical-Induced Disease Detection Using Invariance-based Pattern Learning Model—0
Identifying Protein-protein Interactions in Biomedical Literature using Recurrent Neural Networks with Long Short-Term Memory—0
Deep Learning in Lexical Analysis and Parsing—0
Addressing Domain Adaptation for Chinese Word Segmentation with Global Recurrent Structure—0
Enhancing Drug-Drug Interaction Classification with Corpus-level Feature and Classifier Ensemble—0
End-to-End Optimized Speech Coding with Deep Neural Networks—0
Deep Health Care Text Classification—0
Solving the "false positives" problem in fraud predictionCode0
Clickbait Detection in Tweets Using Self-attentive NetworkCode0
End-to-end Network for Twitter Geolocation Prediction and HashingCode0
A Unified Neural Network Approach for Estimating Travel Time and Distance for a Taxi Trip—0
Identifying Quantum Phase Transitions with Adversarial Neural NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified