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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1251–1300 of 1706 papers

TitleStatusHype
Talla at SemEval-2018 Task 7: Hybrid Loss Optimization for Relation Classification using Convolutional Neural Networks—0
THU\_NGN at SemEval-2018 Task 3: Tweet Irony Detection with Densely connected LSTM and Multi-task LearningCode0
Multi-Scale DenseNet-Based Electricity Theft Detection—0
A Brand-level Ranking System with the Customized Attention-GRU Model—0
Multi-Statistic Approximate Bayesian Computation with Multi-Armed Bandits—0
Sentiment Analysis of Arabic Tweets: Feature Engineering and A Hybrid Approach—0
Extended pipeline for content-based feature engineering in music genre recognition—0
Multi-View Semantic Labeling of 3D Point Clouds for Automated Plant Phenotyping—0
Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models—0
Reusable workflows for gender prediction—0
Attention for Implicit Discourse Relation Recognition—0
PyRATA, Python Rule-based feAture sTructure AnalysisCode0
RULLS: Randomized Union of Locally Linear Subspaces for Feature Engineering—0
DeepTriangle: A Deep Learning Approach to Loss ReservingCode0
Data-Driven Investigative Journalism For Connectas Dataset—0
False Information on Web and Social Media: A SurveyCode0
A machine learning model for identifying cyclic alternating patterns in the sleeping brain—0
Event Extraction with Generative Adversarial Imitation Learning—0
A Deep Representation Empowered Distant Supervision Paradigm for Clinical Information Extraction—0
Learning to Extract Coherent Summary via Deep Reinforcement Learning—0
Incorporating Dictionaries into Deep Neural Networks for the Chinese Clinical Named Entity Recognition—0
DeepFM: An End-to-End Wide & Deep Learning Framework for CTR PredictionCode0
A Simple and Effective Approach to the Story Cloze Test—0
PotentialNet for Molecular Property Prediction—0
An Unsupervised Model with Attention Autoencoders for Question Retrieval—0
Extractive Text Summarization using Neural Networks—0
Interpreting Complex Regression Models—0
Global Pose Estimation with an Attention-based Recurrent Network—0
Event Nugget Detection with Forward-Backward Recurrent Neural Networks—0
Democratizing AI: Non-expert design of prediction tasks—0
client2vec: Towards Systematic Baselines for Banking Applications—0
URLNet: Learning a URL Representation with Deep Learning for Malicious URL DetectionCode0
Predicting Customer Churn: Extreme Gradient Boosting with Temporal DataCode0
Online Compact Convexified Factorization Machine—0
Heuristic Feature Selection for Clickbait Detection—0
Cross-type Biomedical Named Entity Recognition with Deep Multi-Task LearningCode0
Evaluating approaches for supervised semantic labelingCode0
News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions—0
Semi-Supervised Convolutional Neural Networks for Human Activity Recognition—0
Query2Vec: An Evaluation of NLP Techniques for Generalized Workload Analytics—0
A Pipeline for Post-Crisis Twitter Data Acquisition—0
Neural Feature Learning From Relational Database—0
HeNet: A Deep Learning Approach on Intel^ Processor Trace for Effective Exploit Detection—0
aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching ModelCode0
Learning Feature Representations for Keyphrase Extraction—0
A Deep Belief Network Based Machine Learning System for Risky Host Detection—0
Learning Representations from Road Network for End-to-End Urban Growth Simulation—0
On the Benefit of Combining Neural, Statistical and External Features for Fake News IdentificationCode0
ATM: A distributed, collaborative, scalable system for automated machine learningCode0
SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical PropertiesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified