文献
J-GLOBAL ID:202202231337530630
整理番号:22A0793967
クラス不均衡音声病理学分類:最適2因子ランダムフォレストとのハイブリッドサンプリングの結合【JST・京大機械翻訳】
Class-imbalanced voice pathology classification: Combining hybrid sampling with optimal two-factor random forests
著者 (7件):
Zhang Xiaojun
(School of Electronic and Information Engineering, Soochow University, Suzhou 215000, China)
,
Zhang Xiaojun
(School of Optoelectronic Science and Engineering, Soochow University, Suzhou 215000, China)
,
Zhou Changwei
(School of Optoelectronic Science and Engineering, Soochow University, Suzhou 215000, China)
,
Zhu Xincheng
(School of Optoelectronic Science and Engineering, Soochow University, Suzhou 215000, China)
,
Tao Zhi
(School of Electronic and Information Engineering, Soochow University, Suzhou 215000, China)
,
Tao Zhi
(School of Optoelectronic Science and Engineering, Soochow University, Suzhou 215000, China)
,
Zhao Heming
(School of Electronic and Information Engineering, Soochow University, Suzhou 215000, China)
資料名:
Applied Acoustics
(Applied Acoustics)
巻:
190
ページ:
Null
発行年:
2022年
JST資料番号:
D0559A
ISSN:
0003-682X
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)