Large-Scale Disk Failure Prediction [[electronic resource] ] : PAKDD 2020 Competition and Workshop, AI Ops 2020, February 7 – May 15, 2020, Revised Selected Papers / / edited by Cheng He, Mengling Feng, Patrick P. C. Lee, Pinghui Wang, Shujie Han, Yi Liu |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
Descrizione fisica | 1 online resource (X, 143 p. 96 illus., 40 illus. in color.) |
Disciplina | 006.3 |
Collana | Communications in Computer and Information Science |
Soggetto topico |
Data mining
Computer organization Microprogramming Artificial intelligence Data Mining and Knowledge Discovery Computer Systems Organization and Communication Networks Control Structures and Microprogramming Artificial Intelligence |
ISBN | 981-15-7749-8 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | An Introduction to PAKDD CUP 2020 Dataset -- PAKDD 2020 Alibaba AIOps Competition-Large-scale Disk Failure Prediction: Third Place Team -- A Voting-based Robust Model for Disk Failure Prediction -- First place solution of PAKDD Cup 2020 -- Anomaly Detection of Hard Disk Drives based on Multi-scale Feature -- Disk Failure Prediction: an in-depth comparison between deep neural networks and tree-based models -- PAKDD2020 Alibaba AI Ops Competition: Large-Scale Disk Failure Prediction -- SHARP: SMART HDD Anomaly Risk Prediction -- Tree-based model with advanced data preprocessing for large scale hard disk failure prediction -- PAKDD2020 Alibaba AI Ops Competition: An SPE-LightGBM Approach -- Noise Feature Selection Method in PAKDD 2020 Alibaba AI Ops Competition: Large-Scale Disk Failure Prediction -- Characterizing and Modeling for Proactive Disk Failure Prediction to Improve Reliability of Data Centers -- Summary of PAKDD CUP 2020: From Organizers’ Perspective. |
Record Nr. | UNISA-996465470003316 |
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
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Large-Scale Disk Failure Prediction : PAKDD 2020 Competition and Workshop, AI Ops 2020, February 7 – May 15, 2020, Revised Selected Papers / / edited by Cheng He, Mengling Feng, Patrick P. C. Lee, Pinghui Wang, Shujie Han, Yi Liu |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
Descrizione fisica | 1 online resource (X, 143 p. 96 illus., 40 illus. in color.) |
Disciplina | 006.3 |
Collana | Communications in Computer and Information Science |
Soggetto topico |
Data mining
Computer organization Microprogramming Artificial intelligence Data Mining and Knowledge Discovery Computer Systems Organization and Communication Networks Control Structures and Microprogramming Artificial Intelligence |
ISBN | 981-15-7749-8 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | An Introduction to PAKDD CUP 2020 Dataset -- PAKDD 2020 Alibaba AIOps Competition-Large-scale Disk Failure Prediction: Third Place Team -- A Voting-based Robust Model for Disk Failure Prediction -- First place solution of PAKDD Cup 2020 -- Anomaly Detection of Hard Disk Drives based on Multi-scale Feature -- Disk Failure Prediction: an in-depth comparison between deep neural networks and tree-based models -- PAKDD2020 Alibaba AI Ops Competition: Large-Scale Disk Failure Prediction -- SHARP: SMART HDD Anomaly Risk Prediction -- Tree-based model with advanced data preprocessing for large scale hard disk failure prediction -- PAKDD2020 Alibaba AI Ops Competition: An SPE-LightGBM Approach -- Noise Feature Selection Method in PAKDD 2020 Alibaba AI Ops Competition: Large-Scale Disk Failure Prediction -- Characterizing and Modeling for Proactive Disk Failure Prediction to Improve Reliability of Data Centers -- Summary of PAKDD CUP 2020: From Organizers’ Perspective. |
Record Nr. | UNINA-9910416083003321 |
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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