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Deep Learning Hyper-parameter Tuning for Sentiment Analysis in Twitter based on Evolutionary Algorithms
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Decision of Neural Networks Hyperparameters with a Population-Based Algorithm
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Learning from Imbalanced Data Sets
inferredcites →https://doi.org/10.1007/bf02295996openalex-snapshot
Note on the Sampling Error of the Difference Between Correlated Proportions or Percentages
inferredcites →https://doi.org/10.1007/s00500-011-0713-4openalex-snapshot
Speeding up the evaluation phase of GP classification algorithms on GPUs
inferredcites →https://doi.org/10.1016/j.jocs.2010.12.007openalex-snapshot
Twitter mood predicts the stock market
inferredcites →https://doi.org/10.1017/s1351324912000332openalex-snapshot
Sentiment analysis in Twitter
inferredcites →https://doi.org/10.1109/ccis.2018.8691381openalex-snapshot
Advanced Combined LSTM-CNN Model for Twitter Sentiment Analysis
inferredcites →https://doi.org/10.1109/cec.2013.6557555openalex-snapshot
Success-history based parameter adaptation for Differential Evolution
inferredcites →https://doi.org/10.1109/cec.2014.6900380openalex-snapshot
Improving the search performance of SHADE using linear population size reduction
inferredcites →https://doi.org/10.1109/slt.2016.7846334openalex-snapshot
Automated structure discovery and parameter tuning of neural network language model based on evolution strategy
inferredcites →https://doi.org/10.1145/1520340.1520584openalex-snapshot
Micro-blogging as online word of mouth branding
inferredcites →https://doi.org/10.1145/2792984openalex-snapshot
Many-Objective Evolutionary Algorithms
inferredcites →https://doi.org/10.1145/3167132.3167325openalex-snapshot
A multi-task neural network for multilingual sentiment classification and language detection on Twitter
inferredcites →https://doi.org/10.1145/3185045openalex-snapshot
The State-of-the-Art in Twitter Sentiment Analysis
inferredcites →https://doi.org/10.1162/106365601750190398openalex-snapshot
Completely Derandomized Self-Adaptation in Evolution Strategies
inferredcites →https://doi.org/10.1162/tacl_a_00051openalex-snapshot
Enriching Word Vectors with Subword Information
inferredcites →https://doi.org/10.1177/0894439311404119openalex-snapshot
Why the Pirate Party Won the German Election of 2009 or The Trouble With Predictions: A Response to Tumasjan, A., Sprenger, T. O., Sander, P. G., & Welpe, I. M. “Predicting Elections With Twitter: What 140 Characters Reveal About Political Sentiment”
inferredcites →https://doi.org/10.1561/1500000011openalex-snapshot
Opinion Mining and Sentiment Analysis
inferredcites →https://doi.org/10.1561/9781601981516openalex-snapshot
Opinion Mining and Sentiment Analysis
inferredcites →https://doi.org/10.1609/icwsm.v4i1.14009openalex-snapshot
Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment
inferredcites →https://doi.org/10.18653/v1/d18-1377openalex-snapshot
IARM: Inter-Aspect Relation Modeling with Memory Networks in Aspect-Based Sentiment Analysis
inferredcites →https://doi.org/10.18653/v1/s17-2094openalex-snapshot
BB_twtr at SemEval-2017 Task 4: Twitter Sentiment Analysis with CNNs and LSTMs
inferredcites →https://doi.org/10.18653/v1/w18-6219openalex-snapshot
Self-Attention: A Better Building Block for Sentiment Analysis Neural Network Classifiers
inferredcites →https://doi.org/10.26342/2019-62-9openalex-snapshot
TASS 2018: The Strength of Deep Learning in Language Understanding Tasks
inferredcites →https://doi.org/10.2991/ijcis.2017.10.1.38openalex-snapshot
A snapshot of image pre-processing for convolutional neural networks: case study of MNIST
inferredcites →https://doi.org/10.3115/v1/d14-1181openalex-snapshot
Convolutional Neural Networks for Sentence Classification
inferredcites →https://doi.org/10.3390/computers8010004openalex-snapshot
Sentiment Analysis of Lithuanian Texts Using Traditional and Deep Learning Approaches
inferredcites →https://doi.org/10.48550/arxiv.1206.2944openalex-snapshot
Practical Bayesian Optimization of Machine Learning Algorithms
inferredcites →https://doi.org/10.48550/arxiv.1308.6242openalex-snapshot
NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets
inferredcites →https://doi.org/10.48550/arxiv.1604.07269openalex-snapshot
CMA-ES for Hyperparameter Optimization of Deep Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1703.03130openalex-snapshot
A Structured Self-attentive Sentence Embedding
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Comparison of the Indobert Optimization Hyperparameter Algorithm for Radicalism Sentiment Analysis
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Hyperparameter Optimization in Sentiment Analysis Using Reinforcement Learning
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Grid Search Tuning of Hyperparameters in Random Forest Classifier for Customer Feedback Sentiment Prediction
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An extensive analysis of online restaurant reviews: a case study of the Amazonian Culinary Tourism
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Optimization of Machine Learning Algorithms Through Hyper-parameter Tuning Applied for the classification of Arabic news
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Deep Learning Neural Networks in the Cloud
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Hyperparameter Tuning for Machine Learning Algorithms Used for Arabic Sentiment Analysis
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Análisis de sentimientos en Twitter
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