語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
FindBook
Google Book
Amazon
博客來
Applications of Machine Learning to Some Statistical Inference Problems.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Applications of Machine Learning to Some Statistical Inference Problems./
作者:
Gao, Zijun.
面頁冊數:
1 online resource (127 pages)
附註:
Source: Dissertations Abstracts International, Volume: 84-05, Section: B.
Contained By:
Dissertations Abstracts International84-05B.
標題:
Vaccines. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29756333click for full text (PQDT)
ISBN:
9798357511317
Applications of Machine Learning to Some Statistical Inference Problems.
Gao, Zijun.
Applications of Machine Learning to Some Statistical Inference Problems.
- 1 online resource (127 pages)
Source: Dissertations Abstracts International, Volume: 84-05, Section: B.
Thesis (Ph.D.)--Stanford University, 2022.
Includes bibliographical references
With impressive statistical learning techniques, new solutions can be provided to challenging problems in statistics. Statistical questions regarding heterogeneous treatment effects and conditional densities are two such examples.Heterogeneous treatment effects describe the influence of a drug or policy with an emphasis on individual variability. I explored the possibilities of applying machine learning tools to the estimation, inference, and accuracy assessment of heterogeneous treatment effects.Conditional densities characterize how a response depends on a set of covariates and extends conditional means to incorporate information like scale and shape. I developed a series of statistical methods for the conditional density estimation borrowing strengths from decision trees and gradient boosting.Despite the maturity of existing machine learning algorithms, careful modifications are required to adapt standard approaches to non-classification and non-prediction queries with desirable statistical properties.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023
Mode of access: World Wide Web
ISBN: 9798357511317Subjects--Topical Terms:
684854
Vaccines.
Index Terms--Genre/Form:
542853
Electronic books.
Applications of Machine Learning to Some Statistical Inference Problems.
LDR
:02343nmm a2200373K 4500
001
2359865
005
20230917195308.5
006
m o d
007
cr mn ---uuuuu
008
241011s2022 xx obm 000 0 eng d
020
$a
9798357511317
035
$a
(MiAaPQ)AAI29756333
035
$a
(MiAaPQ)STANFORDhb677ff7601
035
$a
AAI29756333
040
$a
MiAaPQ
$b
eng
$c
MiAaPQ
$d
NTU
100
1
$a
Gao, Zijun.
$3
3700480
245
1 0
$a
Applications of Machine Learning to Some Statistical Inference Problems.
264
0
$c
2022
300
$a
1 online resource (127 pages)
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
500
$a
Source: Dissertations Abstracts International, Volume: 84-05, Section: B.
500
$a
Advisor: Tibshirani, Robert; Wager, Stefan; Hastie, Trevor.
502
$a
Thesis (Ph.D.)--Stanford University, 2022.
504
$a
Includes bibliographical references
520
$a
With impressive statistical learning techniques, new solutions can be provided to challenging problems in statistics. Statistical questions regarding heterogeneous treatment effects and conditional densities are two such examples.Heterogeneous treatment effects describe the influence of a drug or policy with an emphasis on individual variability. I explored the possibilities of applying machine learning tools to the estimation, inference, and accuracy assessment of heterogeneous treatment effects.Conditional densities characterize how a response depends on a set of covariates and extends conditional means to incorporate information like scale and shape. I developed a series of statistical methods for the conditional density estimation borrowing strengths from decision trees and gradient boosting.Despite the maturity of existing machine learning algorithms, careful modifications are required to adapt standard approaches to non-classification and non-prediction queries with desirable statistical properties.
533
$a
Electronic reproduction.
$b
Ann Arbor, Mich. :
$c
ProQuest,
$d
2023
538
$a
Mode of access: World Wide Web
650
4
$a
Vaccines.
$3
684854
650
4
$a
Statistical inference.
$3
3700481
650
4
$a
Gene expression.
$3
643979
650
4
$a
Algorithms.
$3
536374
650
4
$a
Precision medicine.
$3
3661411
650
4
$a
Medical research.
$2
bicssc
$3
1556686
650
4
$a
Bioinformatics.
$3
553671
650
4
$a
Computer science.
$3
523869
650
4
$a
Genetics.
$3
530508
650
4
$a
Medicine.
$3
641104
655
7
$a
Electronic books.
$2
lcsh
$3
542853
690
$a
0800
690
$a
0715
690
$a
0984
690
$a
0369
690
$a
0564
710
2
$a
ProQuest Information and Learning Co.
$3
783688
710
2
$a
Stanford University.
$3
754827
773
0
$t
Dissertations Abstracts International
$g
84-05B.
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29756333
$z
click for full text (PQDT)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9482221
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入