{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T22:06:11Z","timestamp":1775513171381,"version":"3.50.1"},"reference-count":45,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,12]]},"DOI":"10.1109\/bigdata47090.2019.9006542","type":"proceedings-article","created":{"date-parts":[[2020,2,25]],"date-time":"2020-02-25T06:05:34Z","timestamp":1582610734000},"page":"5844-5853","source":"Crossref","is-referenced-by-count":6,"title":["Solar Flare Prediction Using Two-tier Ensemble with Deep Learning and Gradient Boosting Machine"],"prefix":"10.1109","author":[{"given":"Chau","family":"Pham","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vung","family":"Pham","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tommy","family":"Dang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"100","article-title":"Mtdes: Multi-dimensional temporal data exploration system; strong support for exploratory analysis award in vast 2018, mini-challenge 2","author":"pham","year":"0","journal-title":"2018 IEEE Conference on Visual Analytics Science and Technology (VAST)"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622375"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622097"},{"key":"ref32","year":"2015","journal-title":"National Space Weather Action Plan"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1029\/2018SW001861"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.elerap.2018.08.002"},{"key":"ref37","author":"pham","year":"2019","journal-title":"Outliagnostics Visualizing temporal discrepancy in outlying signatures of data entries"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8622092"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3847\/1538-4357\/835\/2\/156"},{"key":"ref34","article-title":"Predict Saturated Thickness using TensorBoard Visualization","author":"nguyen","year":"2018","journal-title":"Workshop on Visualisation in Environmental Sciences (EnvirVis)"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2012.128"},{"key":"ref40","first-page":"6638","article-title":"Catboost: Unbiased boosting with categorical features","volume":"2018 december","author":"prokhorenkova","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref11","year":"2019","journal-title":"Multivariate time series dataset for space weather data analytics"},{"key":"ref12","year":"2019","journal-title":"Solar flare prediction from time series of solar magnetic field parameters"},{"key":"ref13","year":"2019","journal-title":"Solar flare prediction from time series of solar magnetic field parameters Description of the Data"},{"key":"ref14","author":"fox","year":"2019","journal-title":"Solar Flares What Does It Take to Be X-Class"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy Function Approximation: A gradient Boosting Machine","volume":"29","author":"friedman","year":"2001","journal-title":"The Annals of Statistics"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/S1352-2310(97)00447-0"},{"key":"ref17","first-page":"345","article-title":"A probabilistic interpretation of precision, recall and f-score, with implication for evaluation","author":"goutte","year":"2005","journal-title":"European Conference on Information Retrieval"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2017.8258213"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref28","first-page":"4765","article-title":"A unified approach to interpreting model predictions","author":"lundberg","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref4","author":"bobra","year":"2019","journal-title":"Spaceweather HMI Active Region Patch (SHARP)"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3847\/1538-4357\/ab1b3c"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1088\/2041-8205\/747\/2\/L41"},{"key":"ref6","article-title":"Solar flare forecasting: A novel deep learning approach","author":"cai","year":"2018","journal-title":"AGU Fall Meeting Abstracts"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2017.8258216"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1088\/0004-637X\/798\/2\/135"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11207-006-0077-6"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.12942\/lrsp-2008-1"},{"key":"ref9","article-title":"WordStream: Interactive Visualization for Topic Evolution","author":"dang","year":"2019","journal-title":"EuroVis 2019 - Short Papers"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"64a","DOI":"10.1051\/0004-6361\/201525978","article-title":"An automated classification approach to ranking photospheric proxies of magnetic energy build-up","volume":"579","author":"al-ghraibah","year":"2015","journal-title":"Astronomy & Astrophysics"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1086\/503895"},{"key":"ref45","first-page":"307","article-title":"The Fundamental Nature of the Log Loss Function","volume":"9300","author":"vovk","year":"2015","journal-title":"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)"},{"key":"ref22","first-page":"3147","article-title":"LightGBM: A highly efficient gradient boosting decision tree","author":"ke","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref21","first-page":"3146","article-title":"Lightgbm: A highly efficient gradient boosting decision tree","author":"ke","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref42","first-page":"1","author":"rogozhnikov","year":"2017","journal-title":"InfiniteBoost building infinite ensembles with gradient descent"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"32","DOI":"10.25080\/Majora-14bd3278-006","article-title":"Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-Learn","author":"komer","year":"2014","journal-title":"Proceedings of the 13th Python in Science Conference"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/s11207-006-0272-5"},{"key":"ref23","article-title":"Jupyter notebooks - a publishing format for reproducible computational workflows","author":"kluyver","year":"2016","journal-title":"ELPUB"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s11207-008-9288-3"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1086\/377512"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1086\/511857"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1520\/SSMS20190029"}],"event":{"name":"2019 IEEE International Conference on Big Data (Big Data)","location":"Los Angeles, CA, USA","start":{"date-parts":[[2019,12,9]]},"end":{"date-parts":[[2019,12,12]]}},"container-title":["2019 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8986695\/9005444\/09006542.pdf?arnumber=9006542","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T21:47:56Z","timestamp":1658094476000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9006542\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/bigdata47090.2019.9006542","relation":{},"subject":[],"published":{"date-parts":[[2019,12]]}}}