Results 71 to 80 of about 2,020,230 (285)

Improved Guarantees for k-means++ and k-means++ Parallel

, 2020
In this paper, we study k-means++ and k-means++ parallel, the two most popular algorithms for the classic k-means clustering problem. We provide novel analyses and show improved approximation and bi-criteria approximation guarantees for k-means++ and k-means++ parallel.
Makarychev, Konstantin, Reddy, Aravind, Shan, Liren   +2 more
openaire   +2 more sources

Randomized Dimensionality Reduction for k-means Clustering [PDF]

, 2013
We study the topic of dimensionality reduction for $k$-means clustering. Dimensionality reduction encompasses the union of two approaches: \emph{feature selection} and \emph{feature extraction}.
Boutsidis, Christos, Drineas, Petros, Mahoney, Michael W., Zouzias, Anastasios   +3 more
core  

Distributed Kernel K-Means for Large Scale Clustering

, 2017
Clustering samples according to an effective metric and/or vector space representation is a challenging unsupervised learning task with a wide spectrum of applications.
Decherchi, Sergio, Ferrarotti, Marco Jacopo, Rocchia, Walter   +2 more
core   +1 more source

The Fate (Outcome) of Clinically Apparent Single Lesion and Oligofocal Nephroblastomatosis Treated According to SIOP/GPOH Protocols for Wilms Tumor

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background The management of clinically apparent single lesions or oligofocal nephroblastomatosis, a facultative precursor of nephroblastoma, remains debated. Methods We retrospectively analyzed 37 patients with clinically apparent single or oligofocal nephroblastomatosis (two to three lesions per kidney) among 2347 patients registered between
Nils Welter, Jens‐Peter Schenk, Jenny Wegert, Manfred Gessler, Leo Kager, Stefan Wagenpfeil, Marina Müller, Jean‐Michel Wolff, Joerg Fuchs, Steven W. Warmann, Clemens‐Magnus Meier, Jochen Hubertus, Christian Rübe, Christian Vokuhl, Patrick Melchior, Lena Tschirner, Norbert Graf, Rhoikos Furtwängler   +17 more
wiley   +1 more source

k-Means [PDF]

, 2023
The k-means clustering algorithm (k-means for short) provides a method offinding structure in input examples. It is also called the Lloyd–Forgy algorithm as it was independently introduced by both Stuart Lloyd and Edward Forgy. k-means, like other algorithms you will study in this part of the book, is an unsupervised learning algorithm and, as such ...
openaire  

Inpatient Food Insecurity and Pediatric Hematology Oncology Hospitalization Outcomes

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Children with cancer and blood disorders are at risk for food insecurity (FI). We aimed to describe the association of inpatient food insecurity (IFI) and hospitalization outcomes among patients admitted to the pediatric hematology oncology service. Of 325 caregivers screened for IFI, 60 (18.6%) screened positive.
Joanna M. Robles, Greg Russell, Leila H. DeWitt, Kimberly Montez, Callie L. Brown   +4 more
wiley   +1 more source

A Improving House Price Clustering Results with K-means through the Implementation of One-hot Encoding Pre-processing Technique

Journal of Applied Informatics and Computing
Basic human needs include a house that serves as a place to live and a shelter from everything. In Indonesia, owning a house is still a challenging aspect due to its high price.
Vicka Rizqi Maulani, Mula Agung Barata, Pelangi Eka Yuwita   +2 more
doaj   +1 more source

Germline TP53 Mutations Causing Diamond–Blackfan Anemia: A French Report

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Diamond–Blackfan anemia is a rare congenital erythroblastopenia typically caused by mutations in ribosomal protein genes. Recently, gain‐of‐function mutations in TP53 have been identified as a novel cause of Diamond–Blackfan anemia. We report two French patients who both harbored a heterozygous TP53 deletion (NM_000546.5: c.1077delA; p ...
Rafael Moisan, Lydie Da Costa, Ludivine David Nguyen, Heloise Chosseler, Audrey Riquet, Benedicte Bruno, Melissa Barbati   +6 more
wiley   +1 more source

Health‐Related Quality of Life and Symptom Severity Among Patients With PIK3CA‐Related Overgrowth Spectrum: A Mixed‐Methods Study to Understand Real‐World Experience With Alpelisib Treatment

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background PIK3CA‐related overgrowth spectrum (PROS) includes several rare overgrowth disorders resulting from somatic gain‐of‐function mutations in PIK3CA. Despite treatment advances, including the recent approval of alpelisib for PROS in the United States, literature detailing the patient experience with PROS is limited.
Vamsi Bollu, Kaitlin LaGasse, Cory D. Saucier, Kimberly Raymond, Miranda Lauher‐Charest, Lauren Crowder, Beilei Cai, Mary Lisha Paul, Denise Adams   +8 more
wiley   +1 more source

K-means** - a fast and efficient K-means algorithms

International Journal of Intelligent Information and Database Systems, 2018
K-means often converges to a local optimum. In improved versions of K-means, k-means++ is well-known for achieving a rather optimum solution with its cluster initialisation strategy and high computational efficiency. Incremental K-means is recognised for its converging to the empirically global optimum but having a high complexity due to its stepping ...
Cuong Duc Nguyen, Trong Hai Duong
openaire   +1 more source