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 851–900 of 1706 papers

TitleStatusHype
DeepLink: A Novel Link Prediction Framework based on Deep Learning—0
DeepMiner at SemEval-2018 Task 1: Emotion Intensity Recognition Using Deep Representation Learning—0
deepMiRGene: Deep Neural Network based Precursor microRNA Prediction—0
Deep Neural Baselines for Computational Paralinguistics—0
Deep Neural Mobile Networking—0
Deep Neural Solver for Math Word Problems—0
DeepNNNER: Applying BLSTM-CNNs and Extended Lexicons to Named Entity Recognition in Tweets—0
Deepr: A Convolutional Net for Medical Records—0
Deep Ranking for Person Re-identification via Joint Representation Learning—0
Deep Recurrent Neural Network for Protein Function Prediction from Sequence—0
Deep Representation Learning in Speech Processing: Challenges, Recent Advances, and Future Trends—0
DeepSoft: A vision for a deep model of software—0
Deep Style Match for Complementary Recommendation—0
DeepVar: An End-to-End Deep Learning Approach for Genomic Variant Recognition in Biomedical Literature—0
Defect Detection in Tire X-Ray Images: Conventional Methods Meet Deep Structures—0
DENS-ECG: A Deep Learning Approach for ECG Signal Delineation—0
Dependency-based Gated Recursive Neural Network for Chinese Word Segmentation—0
Depth Selection for Deep ReLU Nets in Feature Extraction and Generalization—0
Design & Implementation of Automatic Machine Condition Monitoring and Maintenance System in Limited Resource Situations—0
Designing Adversarially Resilient Classifiers using Resilient Feature Engineering—0
Design of Recognition and Evaluation System for Table Tennis Players' Motor Skills Based on Artificial Intelligence—0
Detecting Attacks on IoT Devices using Featureless 1D-CNN—0
Detecting Troll Tweets in a Bilingual Corpus—0
Detection of Product Comparisons - How Far Does an Out-of-the-Box Semantic Role Labeling System Take You?—0
Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models—0
Determining whether the non-protein-coding DNA sequences are in a complex interactive relationship by using an artificial intelligence method—0
Diagnosis of Parkinson's Disease Using EEG Signals and Machine Learning Techniques: A Comprehensive Study—0
Differentiable Sparsification for Deep Neural Networks—0
Differentiable Sparsification for Deep Neural Networks—0
Discourse Parsing with Attention-based Hierarchical Neural Networks—0
Distilled Mid-Fusion Transformer Networks for Multi-Modal Human Activity Recognition—0
Distinguishing Risk Preferences using Repeated Gambles—0
Distributed Multi-Head Learning Systems for Power Consumption Prediction—0
DLinear-based Prediction of Remaining Useful Life of Lithium-Ion Batteries: Feature Engineering through Explainable Artificial Intelligence—0
DNN2LR: Automatic Feature Crossing for Credit Scoring—0
Do LSTMs really work so well for PoS tagging? -- A replication study—0
Don't Throw Those Morphological Analyzers Away Just Yet: Neural Morphological Disambiguation for Arabic—0
Downsampling and geometric feature methods for EEG classification tasks with CNNs—0
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling—0
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation—0
DROCC: Deep Robust One-Class Classification—0
Dropout Prediction over Weeks in MOOCs via Interpretable Multi-Layer Representation Learning—0
Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers—0
Dual Training and Dual Prediction for Polarity Classification—0
DUBLIN -- Document Understanding By Language-Image Network—0
DUTH at SemEval-2017 Task 5: Sentiment Predictability in Financial Microblogging and News Articles—0
DUTIR in BioNLP-ST 2016: Utilizing Convolutional Network and Distributed Representation to Extract Complicate Relations—0
Dynamic Adaptation in Data Storage: Real-Time Machine Learning for Enhanced Prefetching—0
Dynamic and Adaptive Feature Generation with LLM—0
Dynamic Facial Analysis: From Bayesian Filtering to Recurrent Neural Network—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified