Web-Books
im Austria-Forum
Austria-Forum
Web-Books
Tagungsbände
Intelligent Environments 2019 - Workshop Proceedings of the 15th International Conference on Intelligent Environments
Seite - 45 -
  • Benutzer
  • Version
    • Vollversion
    • Textversion
  • Sprache
    • Deutsch
    • English - Englisch

Seite - 45 - in Intelligent Environments 2019 - Workshop Proceedings of the 15th International Conference on Intelligent Environments

Bild der Seite - 45 -

Bild der Seite - 45 - in Intelligent Environments 2019 - Workshop Proceedings of the 15th International Conference on Intelligent Environments

Text der Seite - 45 -

Figure2. ROCCurveComparison. In the future,weconsider strengthening thequalityofdata, suchas considering the cyclicality of the economy, so that the data covers at least one full economic cycle, and collectingmoreunstructured trainingdata tomakemore complexdeep learningmodels applicable.Alsowewouldconsidermoreeconomicsimplications,suchasdistinguishing between thedifferent effectsofmonetaryandfiscalpolicieson theadequacyofcapital. References [1] DiamondDW,DybvigPH.Bankruns,deposit insurance,andliquidity[J]. Journalofpoliticaleconomy, 1983,91(3):401-419. [2] Liquidity riskmeasurement andmanagement: a practitioner’s guide to global best practices[M]. John Wiley&Sons,2006. [3] Batra R,Daudpota SM. Integrating StockTwitswith sentiment analysis for better prediction of stock pricemovement[C]2018 InternationalConferenceonComputing,Mathematics andEngineeringTech- nologies (iCoMET). IEEE,2018:1-5. [4] FengF,ChenH,HeX,etal. ImprovingStockMovementPredictionwithAdversarialTraining[J]. arXiv preprint arXiv:1810.09936,2018. [5] DingX, ZhangY, Liu T, et al. Using structured events to predict stock pricemovement: An empiri- cal investigation[C]//Proceedings of the 2014Conference onEmpiricalMethods inNatural Language Processing (EMNLP).2014:1415-1425. [6] SundermeyerM,SchluterR,NeyH.LSTMneural networks for languagemodeling[C]//Thirteenth an- nual conferenceof the international speechcommunicationassociation.2012. [7] TiantianWang, ”Researchof feature selection and feature extractionmethods in internet news classifi- cation”,universityof scienceand technologyofchina,2016. [8] GoldbergY,LevyO.word2vecExplained:derivingMikolovetal.’snegative-samplingword-embedding method[J]. arXivpreprint arXiv:1402.3722,2014. [9] Soucy P, Mineau G W. Beyond TFIDF weighting for text categorization in the vector space mod- el[C]//IJCAI.2005,5:1130-1135. [10] TangJ,DengC,HuangGB.Extreme learningmachine formultilayerperceptron[J]. IEEEtransactions onneuralnetworksand learningsystems,2016,27(4):809-821. [11] MetzCE,HermanBA,RoeCA. Statistical comparison of twoROC-curve estimates obtained from partially-paireddatasets[J].MedicalDecisionMaking,1998,18(1):110-121. [12] ZhouZH.MachineLearning[M].Beijing:TsinghuaUniversityPress, 2016:23-51. Y.Duetal. /Predicting the InterbankCapitalAdequacyLevelBasedonFinancialDataAnalysis 45
zurück zum  Buch Intelligent Environments 2019 - Workshop Proceedings of the 15th International Conference on Intelligent Environments"
Intelligent Environments 2019 Workshop Proceedings of the 15th International Conference on Intelligent Environments
Titel
Intelligent Environments 2019
Untertitel
Workshop Proceedings of the 15th International Conference on Intelligent Environments
Autoren
Andrés Muñoz
Sofia Ouhbi
Wolfgang Minker
Loubna Echabbi
Miguel Navarro-Cía
Verlag
IOS Press BV
Datum
2019
Sprache
deutsch
Lizenz
CC BY-NC 4.0
ISBN
978-1-61499-983-6
Abmessungen
16.0 x 24.0 cm
Seiten
416
Kategorie
Tagungsbände
Web-Books
Bibliothek
Datenschutz
Impressum
Austria-Forum
Austria-Forum
Web-Books
Intelligent Environments 2019