Results 221 to 230 of about 386,750 (261)
Some of the next articles are maybe not open access.
2014
Introduction Two primary techniques for dimension-reducing feature extraction are subspace projection and feature selection . This chapter will explore the key subspace projection approaches, i.e. PCA and KPCA. (i) Section 3.2 provides motivations for dimension reduction by pointing out (1) the potential adverse effect of large feature ...
openaire +1 more source
Introduction Two primary techniques for dimension-reducing feature extraction are subspace projection and feature selection . This chapter will explore the key subspace projection approaches, i.e. PCA and KPCA. (i) Section 3.2 provides motivations for dimension reduction by pointing out (1) the potential adverse effect of large feature ...
openaire +1 more source
Geodesic PCA versus Log-PCA of Histograms in the Wasserstein Space
SIAM Journal on Scientific Computing, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Elsa Cazelles +4 more
openaire +2 more sources
The Clinical Journal of Pain, 1990
Patients (n = 120) undergoing major orthopedic (e.g., total hip replacement), urologic (e.g., radical prostatectomy), or gynecologic (e.g., total abdominal hysterectomy) procedures were randomly assigned to receive either morphine or oxymorphone postoperatively using a patient-controlled analgesic (PCA) delivery system.
openaire +2 more sources
Patients (n = 120) undergoing major orthopedic (e.g., total hip replacement), urologic (e.g., radical prostatectomy), or gynecologic (e.g., total abdominal hysterectomy) procedures were randomly assigned to receive either morphine or oxymorphone postoperatively using a patient-controlled analgesic (PCA) delivery system.
openaire +2 more sources
Robust PCAs and PCA Using Generalized Mean
2017In this chapter, a robust principal component analysis (PCA) is described, which can overcome the problem that PCA is prone to outliers included in training set. Different from the other alternatives which commonly replace \(L_{2}\)-norm by other distance measures, our method alleviates the negative effect of outliers using the characteristic of the ...
Jiyong Oh, Nojun Kwak
openaire +1 more source
Forecasting crude oil prices: A scaled PCA approach
Energy Economics, 2021Yudong Wang, Yaojie Zhang, Mengxi He
exaly
Scaled PCA: A New Approach to Dimension Reduction
Management Science, 2022Guofu Zhou, Fuwei Jiang, Dashan Huang
exaly

