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 1601–1650 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
ICRC-HIT: A Deep Learning based Comment Sequence Labeling System for Answer Selection Challenge—0
Relation Extraction: Perspective from Convolutional Neural Networks—0
Multi-View Feature Engineering and Learning—0
TwitterHawk: A Feature Bucket Based Approach to Sentiment Analysis—0
IOA: Improving SVM Based Sentiment Classification Through Post Processing—0
INESC-ID: Sentiment Analysis without Hand-Coded Features or Linguistic Resources using Embedding Subspaces—0
Deep Ranking for Person Re-identification via Joint Representation Learning—0
Extracting Human Temporal Orientation from Facebook Language—0
Empty Category Detection With Joint Context-Label Embeddings—0
High-Order Low-Rank Tensors for Semantic Role Labeling—0
Representation Learning for Aspect Category Detection in Online Reviews—0
Personalized Web Search—0
Deep Learning for Answer Sentence SelectionCode0
DeepEdge: A Multi-Scale Bifurcated Deep Network for Top-Down Contour Detection—0
Machine-guided Solution to Mathematical Word Problems—0
Automatic Inference of the Tense of Chinese Events Using Implicit Linguistic Information—0
Neural Networks Leverage Corpus-wide Information for Part-of-speech Tagging—0
Capturing ``attrition intensifying'' structural traits from didactic interaction sequences of MOOC learners—0
A Model of Coherence Based on Distributed Sentence Representation—0
Word Translation Prediction for Morphologically Rich Languages with Bilingual Neural Networks—0
The Randomized Causation Coefficient—0
Feature Engineering for Map Matching of Low-Sampling-Rate GPS Trajectories in Road Network—0
SA-UZH: Verb-based Sentiment Analysis—0
CMUQ-Hybrid: Sentiment Classification By Feature Engineering and Parameter Tuning—0
CMUQ@Qatar:Using Rich Lexical Features for Sentiment Analysis on Twitter—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CNN14 gestures accuracy0.98—Unverified