Results 141 to 150 of about 940,524 (345)

A rate of convergence in clustering analysis [PDF]

, 1992
We present a result about stochastic boundedness of stable empirical processes on Vapnik-Cervonenkis classes of functions and we apply it to obtain a rate of convergence for the approximation between the sample and the populational variation in the k ...
Romo, Juan
core  

Optimasi Pengelompokan Data Pada Metode K-means dengan Analisis Outlier

Jurnal Teknologi dan Sistem Informasi, 2019
Data mining secara umum adalah proses analisis dan eksplorasi sejumlah besar data yang berbeda untuk menemukan pola yang bermakna. . Berbagai teknik tersedia dalam data mining untuk ekstraksi pengetahuan antara lain klasifikasi, prediksi, estimasi ...
Pasek Agus Ariawan
doaj   +1 more source

An efficient k′-means clustering algorithm

Pattern Recognition Letters, 2008
This paper introduces k'-means algorithm that performs correct clustering without pre-assigning the exact number of clusters. This is achieved by minimizing a suggested cost-function. The cost-function extends the mean-square-error cost-function of k-means. The algorithm consists of two separate steps.
openaire   +2 more sources

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

Molecular Oncology, EarlyView.
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova, Michele Montrone, Uday Rangaswamy, Francesco Diversi, Irene Schiavo, Denise Ferrarini, Roberta Di Florio, Irene Longo, Michele Coscia, Nicola Zamboni, Giorgia Demontis, Lisa Veghini, Vincenzo Corbo, Remo Sanges, Paul Heppenstall   +14 more
wiley   +1 more source

A Weighted Sum Validity Function for Clustering with a Hybrid Niching Genetic Algorithm

, 2005
Clustering is inherently a difficult problem, both with respect to the construction of adequate objective functions as well as to the optimization of the objective functions.
Liu, X, Zhang, Leishi, Weiguo Sheng, Stephen Swift, Xiaohui Liu, Zhang, L, Sheng, Weiguo, Sheng, W, Swift, S, Swift, S., Leishi Zhang, Liu, Xiaohui   +11 more
core   +1 more source

Enhancing the performance of gradient boosting trees on regression problems

Journal of Big Data
Gradient Boosting Trees (GBT) is a powerful machine learning technique that is based on ensemble learning methods that leverage the idea of boosting. GBT combines multiple weak learners sequentially to boost its prediction power proving its outstanding ...
Lydia Wahid Rizkallah
doaj   +1 more source

Differential expression of cancer‐related genes supports prediction of poor response to first‐line treatments in T‐ALL pediatric patients with high minimal residual disease

Molecular Oncology, EarlyView.
In the present work, we have identified a transcriptional signature based on the differential expression of six genes (BCL2&MAST4, HSH2D&LAT2, METRN&PITPNM2) that would facilitate the early detection of T‐cell acute lymphoblastic leukemia (T‐ALL) patients prone to a poor treatment response and could be implemented at diagnosis, along with other risk ...
Antonio Lahera, Laura Vela‐Martín, Pablo Fernández‐Navarro, José Luis López‐Lorenzo, Javier Cornago, Pilar Llamas, Eduardo Pérez‐Gómez, José Luis Marín‐Rubio, Manuel Fresno, Javier Santos, José Fernández‐Piqueras, María Villa‐Morales   +11 more
wiley   +1 more source

Enhancing customer segmentation through factor analysis of mixed data (FAMD)-based approach using K-means and hierarchical clustering algorithms [PDF]

In today’s data-driven business landscape, effective customer segmentation is crucial for enhancing engagement, loyalty, and profitability. Traditional clustering methods often struggle with datasets containing both numerical and categorical variables ...
Hasan, R., Mahmood, S., Sattar, U., Ufeli, C. P.   +3 more
core   +1 more source

Detection of Maize Kernels Breakage Rate Based on K-means Clustering

, 2017
In order to optimize the recognition accuracy of maize kernels breakage detection and improve the detection efficiency of maize kernels breakage, this paper using computer vision technology and detecting of the maize kernels breakage based on K-means ...
Bai XP(白晓平), Wang Z(王卓), Gao L(高雷), Yang L(杨亮)   +3 more
core   +1 more source

CCDC80 suppresses high‐grade serous ovarian cancer migration via negative regulation of B7‐H3

Molecular Oncology, EarlyView.
PAX8 is a lineage‐specific master regulator of transcription in high‐grade serous ovarian cancer (HGSC) progression. We show for the first time that PAX8 facilitates proliferation and metastasis by repressing the cell autonomous tumor suppressor CCDC80 and inducing B7‐H3 expression.
Aya Saleh, Nitzan Medina‐Itzhaki, Milena Chekov, Eden Gal‐Swisa, Roba Gabesh‐Wahabi, Inbar Savyon, Inna Naroditsky, Hilary A. Kenny, Basem Fares, Lina Korsensky, Einav Girsh, Liron Berger, Ruth Perets   +12 more
wiley   +1 more source