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 201–225 of 1706 papers

TitleStatusHype
Deep-HiTS: Rotation Invariant Convolutional Neural Network for Transient DetectionCode0
DeepInf: Social Influence Prediction with Deep LearningCode0
DeepFM: An End-to-End Wide & Deep Learning Framework for CTR PredictionCode0
Do Sentence Interactions Matter? Leveraging Sentence Level Representations for Fake News ClassificationCode0
Deep Learning for Answer Sentence SelectionCode0
Application of Machine Learning in Rock Facies Classification with Physics-Motivated Feature AugmentationCode0
DeepCCI: End-to-end Deep Learning for Chemical-Chemical Interaction PredictionCode0
Deep convolutional forest: a dynamic deep ensemble approach for spam detection in textCode0
Efficient Structured Inference for Transition-Based Parsing with Neural Networks and Error StatesCode0
Egocentric Spatial MemoryCode0
A deep learning framework for Text-independent Writer IdentificationCode0
Deep Affix Features Improve Neural Named Entity RecognizersCode0
Deduplication Over Heterogeneous Attribute Types (D-HAT)Code0
DeepAtom: A Framework for Protein-Ligand Binding Affinity PredictionCode0
Deep Convolutional Neural Network Applied to Electroencephalography: Raw Data vs Spectral FeaturesCode0
Enhancing Glucose Level Prediction of ICU Patients through Hierarchical Modeling of Irregular Time-SeriesCode0
A Simple Fusion of Deep and Shallow Learning for Acoustic Scene ClassificationCode0
Ensemble Learning Applied to Classify GPS Trajectories of Birds into Male or FemaleCode0
A Position-aware Bidirectional Attention Network for Aspect-level Sentiment AnalysisCode0
Estimating Linguistic Complexity for Science TextsCode0
ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworksCode0
Evaluating Large Language Models for Anxiety and Depression Classification using Counseling and Psychotherapy TranscriptsCode0
Data Science Kitchen at GermEval 2021: A Fine Selection of Hand-Picked Features, Delivered Fresh from the OvenCode0
Extracting Parallel Sentences with Bidirectional Recurrent Neural Networks to Improve Machine TranslationCode0
DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment AnalysisCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified