The study aims to estimate the ability of different grouping techniques on categorical response. We try to find out how well do they work? Do they really find clusters when clusters exist? We use Cancer Problems in Living Scales from the ACS as our categorical data variables and lung cancer survivors as our studying group. Five methods of cluster analysis are examined for their accuracy in clustering on both real CPILS dataset and simulated data. The methods include hierarchical cluster analysis (Ward's method), model-based clustering of raw data, model-based clustering of the factors scores from a maximum likelihood factor analysis, model-based clustering of the predicted scores from independent factor analysis, and the method of lat...
<p>Subgroup classification for the 111 lung cancer patients of the GSE3141 dataset using the composi...
Abstract The chapter by Milligan and Hirtle provides an overview of the current state of knowledge i...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
The study aims to estimate the ability of different grouping techniques on categorical response. We ...
In clustering, one may be interested in the classification of similar objects into groups, and one m...
The task of the presented study is to find different disease phenotypes of cancer (breast cancer, ca...
Abstract: Clustering is a partition of data into a group of similar or dissimilar data points and ea...
Symptom Cluster Research is a major topic in Cancer Symptom Science. In spite of the several statist...
Clustering algorithms will, in general, either partition a given data set into a pre-specified numbe...
Background: The big data moniker is nowhere better deserved than to describe the ever-increasing pro...
BackgroundHeterogeneity in Acute Respiratory Distress Syndrome (ARDS), as a consequence of its non-s...
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By o...
For clustering multivariate categorical data, a latent class model-based approach (LCC) with local i...
In this paper we use clustering methods to profile a data base of breast cancer patients, as a basis...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
<p>Subgroup classification for the 111 lung cancer patients of the GSE3141 dataset using the composi...
Abstract The chapter by Milligan and Hirtle provides an overview of the current state of knowledge i...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...
The study aims to estimate the ability of different grouping techniques on categorical response. We ...
In clustering, one may be interested in the classification of similar objects into groups, and one m...
The task of the presented study is to find different disease phenotypes of cancer (breast cancer, ca...
Abstract: Clustering is a partition of data into a group of similar or dissimilar data points and ea...
Symptom Cluster Research is a major topic in Cancer Symptom Science. In spite of the several statist...
Clustering algorithms will, in general, either partition a given data set into a pre-specified numbe...
Background: The big data moniker is nowhere better deserved than to describe the ever-increasing pro...
BackgroundHeterogeneity in Acute Respiratory Distress Syndrome (ARDS), as a consequence of its non-s...
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By o...
For clustering multivariate categorical data, a latent class model-based approach (LCC) with local i...
In this paper we use clustering methods to profile a data base of breast cancer patients, as a basis...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
<p>Subgroup classification for the 111 lung cancer patients of the GSE3141 dataset using the composi...
Abstract The chapter by Milligan and Hirtle provides an overview of the current state of knowledge i...
Cluster study or clustering is the assignment of assigning a set of data into groups called clusters...