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 976–1000 of 1706 papers

TitleStatusHype
Influenza Modeling Based on Massive Feature Engineering and International Flow Deconvolution—0
Transfer Learning from an Auxiliary Discriminative Task for Unsupervised Anomaly Detection—0
See and Read: Detecting Depression Symptoms in Higher Education Students Using Multimodal Social Media DataCode0
DeepAtom: A Framework for Protein-Ligand Binding Affinity PredictionCode0
Classical Machine Learning Techniques in the Search of Extrasolar PlanetsCode0
Interpreting Deep Learning Features for Myoelectric Control: A Comparison with Handcrafted FeaturesCode0
Projective Quadratic Regression for Online Learning—0
Cross-Class Relevance Learning for Temporal Concept Localization—0
Automatic Design of CNNs via Differentiable Neural Architecture Search for PolSAR Image Classification—0
Convolutional Neural Network for Convective Storm Nowcasting Using 3D Doppler Weather Radar Data—0
Learning based Methods for Code Runtime Complexity Prediction—0
A System for Diacritizing Four Varieties of Arabic—0
Semi-Supervised Semantic Role Labeling with Cross-View Training—0
Do Sentence Interactions Matter? Leveraging Sentence Level Representations for Fake News ClassificationCode0
A Survey on Recent Advances in Named Entity Recognition from Deep Learning modelsCode0
Malware Classification using Deep Learning based Feature Extraction and Wrapper based Feature Selection TechniqueCode0
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications—0
RiWalk: Fast Structural Node Embedding via Role IdentificationCode0
Geomancer: An Open-Source Framework for Geospatial Feature Engineering—0
Differentiable Sparsification for Deep Neural Networks—0
A Conditional Generative Model for Predicting Material Microstructures from Processing Methods—0
Character Feature Engineering for Japanese Word Segmentation—0
Intrusion detection systems using classical machine learning techniques versus integrated unsupervised feature learning and deep neural network—0
A Three-dimensional Convolutional-Recurrent Network for Convective Storm Nowcasting—0
Revisiting the Role of Feature Engineering for Compound Type Identification in Sanskrit—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified