Author Correction: ADRML: anticancer drug response prediction using manifold learning
نویسندگان
چکیده
منابع مشابه
Isometric Correction for Manifold Learning
In this paper, we present a method for isometric correction of manifold learning techniques. We first present an isometric nonlinear dimension reduction method. Our proposed method overcomes the issues associated with well-known isometric embedding techniques such as ISOMAP and maximum variance unfolding (MVU), i.e., computational complexity and the geodesic convexity requirement. Based on the ...
متن کاملSupervised Manifold Learning for Media Interestingness Prediction
In this paper, we describe the models designed for automatically selecting multimedia data, e.g., image and video segments, which are considered to be interesting for a common viewer. Specifically, we utilize an existing dimensionality reduction method called Neighborhood MinMax Projections (NMMP) to extract the low-dimensional features for predicting the discrete interestingness labels. Meanwh...
متن کاملAuthor Correction
“Phenotype of asthmatics with increased airway S-nitrosoglutathione reductase activity.” Nadzeya V. Marozkina, Xin-Qun Wang, Vitali Stsiapura, Anne Fitzpatrick, Silvia Carraro, Gregory A. Hawkins, Eugene Bleecker, Deborah Meyers, Nizar Jarjour, Sean B. Fain, Sally Wenzel, William Busse, Mario Castro, Reynold A. Panettieri Jr, Wendy Moore, Stephen J. Lewis, Lisa A. Palmer, Talissa Altes, Eduard ...
متن کاملInteractive Learning Using Manifold Geometry
We present an interactive learning method that enables a user to iteratively refine a regression model. The user examines the output of the model, visualized as the vertical axis of a 2D scatterplot, and provides corrections by repositioning individual data instances to the correct output level. Each repositioned data instance acts as a control point for altering the learned model, using the ge...
متن کاملErratum: Author correction
[This corrects the article on p. 433 in vol. 60, PMID: 28989919.].
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scientific Reports
سال: 2020
ISSN: 2045-2322
DOI: 10.1038/s41598-020-77486-0