[PDF][PDF] The k-means clustering technique: General considerations and implementation in Mathematica
L Morissette, S Chartier - Tutorials in Quantitative Methods for …, 2013 - researchgate.net
Data clustering techniques are valuable tools for researchers working with large databases
of multivariate data. In this tutorial, we present a simple yet powerful one: the k-means …
of multivariate data. In this tutorial, we present a simple yet powerful one: the k-means …
An efficient approximation to the K-means clustering for massive data
Due to the progressive growth of the amount of data available in a wide variety of scientific
fields, it has become more difficult to manipulate and analyze such information. In spite of its …
fields, it has become more difficult to manipulate and analyze such information. In spite of its …
A review on clustering techniques: Creating better user experience for online roadshow
Online roadshow is a relatively new concept that has higher flexibility and scalability
compared to the physical roadshow. This is because online roadshow is accessible through …
compared to the physical roadshow. This is because online roadshow is accessible through …
An efficient k-means clustering filtering algorithm using density based initial cluster centers
KM Kumar, ARM Reddy - Information Sciences, 2017 - Elsevier
Abstract k-means is a preeminent partitional based clustering method that finds k clusters
from the given dataset by computing distances from each point to k cluster centers iteratively …
from the given dataset by computing distances from each point to k cluster centers iteratively …
[PDF][PDF] Data mining in education: A review on the knowledge discovery perspective
ABSTRACT Knowledge Discovery in Databases is the process of finding knowledge in
massive amount of data where data mining is the core of this process. Data mining can be …
massive amount of data where data mining is the core of this process. Data mining can be …
[HTML][HTML] Data mining and medical world: breast cancers' diagnosis, treatment, prognosis and challenges
RJ Oskouei, NM Kor, SA Maleki - American journal of cancer …, 2017 - ncbi.nlm.nih.gov
The amount of data in electronic and real world is constantly on the rise. Therefore,
extracting useful knowledge from the total available data is very important and time …
extracting useful knowledge from the total available data is very important and time …
Uncovering unobserved heterogeneity bias: Measuring mobile banking system success
Mobile banking (MB) involving the use of mobile devices to access bank accounts for
conducting financial transactions has proliferated in recent years but inconsistently among …
conducting financial transactions has proliferated in recent years but inconsistently among …
A Cheap Feature Selection Approach for the K-Means Algorithm
The increase in the number of features that need to be analyzed in a wide variety of areas,
such as genome sequencing, computer vision, or sensor networks, represents a challenge …
such as genome sequencing, computer vision, or sensor networks, represents a challenge …
An efficient K-means clustering algorithm for tall data
The analysis of continously larger datasets is a task of major importance in a wide variety of
scientific fields. Therefore, the development of efficient and parallel algorithms to perform …
scientific fields. Therefore, the development of efficient and parallel algorithms to perform …
Clustering based contact tracing analysis and prediction of SARS-CoV-2 infections
INTRODUCTION: Contact tracing is a method to track the victims, which have been infected
from the host with any particular disease. Therefore, clustering based machine learning …
from the host with any particular disease. Therefore, clustering based machine learning …