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 1601–1625 of 1706 papers

TitleStatusHype
Non-lexical neural architecture for fine-grained POS Tagging—0
Distant Supervision for Relation Extraction via Piecewise Convolutional Neural NetworksCode0
Long Short-Term Memory Neural Networks for Chinese Word Segmentation—0
ReVal: A Simple and Effective Machine Translation Evaluation Metric Based on Recurrent Neural NetworksCode0
Multilingual discriminative lexicalized phrase structure parsing—0
Web Content Extraction - a Meta-Analysis of its Past and Thoughts on its Future—0
Relation Classification via Recurrent Neural NetworkCode0
An Effective Neural Network Model for Graph-based Dependency Parsing—0
Event Detection and Domain Adaptation with Convolutional Neural NetworksCode0
Gated Recursive Neural Network for Chinese Word Segmentation—0
Learning Summary Prior Representation for Extractive Summarization—0
Transition-based Dependency DAG Parsing Using Dynamic Oracles—0
A Dual-Layer Semantic Role Labeling System—0
Predicting Polarities of Tweets by Composing Word Embeddings with Long Short-Term Memory—0
KeLP: a Kernel-based Learning Platform for Natural Language Processing—0
Multi-level Translation Quality Prediction with QuEst++—0
Feature Selection for Short Text Classification using Wavelet Packet Transform—0
Feature Optimization for Constituent Parsing via Neural Networks—0
A Joint Model for Chinese Microblog Sentiment Analysis—0
Incremental Recurrent Neural Network Dependency Parser with Search-based Discriminative Training—0
NCSU-SAS-Ning: Candidate Generation and Feature Engineering for Supervised Lexical Normalization—0
Non-Linear Text Regression with a Deep Convolutional Neural Network—0
NEUDM: A System for Topic-Based Message Polarity Classification—0
Structural Representations for Learning Relations between Pairs of Texts—0
A State-of-the-Art Mention-Pair Model for Coreference Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified