Results 301 to 310 of about 4,503,666 (319)

A hybrid dissimilarity measure for mixed-type data clustering

2021
One of the greatest challenges in clustering mixed-type data is finding the adequate distance function between objects. Most distance metrics work either with continuous only or categorical-only data, but in applications, however, mixed-type data are prevalent in many real-world applications.
openaire   +1 more source

Cancer statistics, 2023

Ca-A Cancer Journal for Clinicians, 2023
Rebecca L Siegel, Kimberly D Miller, Nikita Sandeep Wagle   +2 more
exaly  

Innovations in research and clinical care using patient‐generated health data

Ca-A Cancer Journal for Clinicians, 2020
Aasha I Hoogland, Naomi C Brownstein, Adam P Dicker   +2 more
exaly  

Cancer statistics, 2020

Ca-A Cancer Journal for Clinicians, 2020
Rebecca L Siegel, Kimberly D Miller
exaly  

Cancer statistics, 2019

Ca-A Cancer Journal for Clinicians, 2019
Rebecca L Siegel, Kimberly D Miller
exaly  

Colorectal cancer statistics, 2020

Ca-A Cancer Journal for Clinicians, 2020
Rebecca L Siegel, Kimberly D Miller, Stacey A Fedewa   +2 more
exaly  

Cancer statistics, 2018

Ca-A Cancer Journal for Clinicians, 2018
Rebecca L Siegel, Kimberly D Miller, Ahmedin Jemal Dvm   +2 more
exaly  

Cancer statistics in China, 2015

Ca-A Cancer Journal for Clinicians, 2016
Rongshou Zheng, Peter D Baade, Siwei Zhang   +2 more
exaly  

Cancer statistics, 2016

Ca-A Cancer Journal for Clinicians, 2016
Rebecca L Siegel, Kimberly D Miller
exaly  

k-SubMix: Common Subspace Clustering on Mixed-Type Data

2023
Klein, Mauritius, Leiber, Collin, Böhm, Christian   +2 more
openaire   +2 more sources