التفاصيل البيبلوغرافية
| العنوان: |
The performance of iForest under different contamination parameters in the dataset with a abnormal ratio of 0.32, c represents the contamination parameter. |
| المؤلفون: |
Yifan Feng (132121), Weihong Cai (6866267), Haoyu Yue (12024480), Jianlong Xu (841260), Yan Lin (285018), Jiaxin Chen (1761877), Zijun Hu (11528908) |
| سنة النشر: |
2022 |
| المجموعة: |
Smithsonian Institution: Digital Repository |
| مصطلحات موضوعية: |
Biotechnology, Developmental Biology, Space Science, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Information Systems not elsewhere classified, standard euclidean distance, normal cluster centre, challenging task due, actual industrial environment, achieve secondary filtering, anomaly detection rates, anomaly detection, well applied, training set, scale networks, prior knowledge, notable advantages, network traffic, great influence, experiments showed, abnormal ratio, abnormal points |
| الوصف: |
The performance of iForest under different contamination parameters in the dataset with a abnormal ratio of 0.32, c represents the contamination parameter. |
| نوع الوثيقة: |
still image |
| اللغة: |
unknown |
| Relation: |
https://figshare.com/articles/figure/The_performance_of_iForest_under_different_contamination_parameters_in_the_dataset_with_a_abnormal_ratio_of_0_32_c_represents_the_contamination_parameter_/19097847 |
| DOI: |
10.1371/journal.pone.0263423.g002 |
| الاتاحة: |
https://doi.org/10.1371/journal.pone.0263423.g002 |
| Rights: |
CC BY 4.0 |
| رقم الانضمام: |
edsbas.5D549C42 |
| قاعدة البيانات: |
BASE |