<p>Almost all experimental EST datasets (except T-box dataset) show similar clustering accuracies between the DBSCAN and the hierarchical clustering methods.</p
Abstract. This paper introduces a hybrid hierarchical clustering method, which is a novel method for...
Abstract In this paper we suggest a new index for measuring the distance between two hierarchical cl...
<p>To calculate the pairwise distances for the hierarchical clustering, three commonly used linkage ...
Distance measures play an important role in cluster analysis. There is no single distance measure th...
Common goal of descriptive data mining techniques is presenting new information in concise, easily i...
Common goal of descriptive data mining techniques is presenting new information in concise, easily i...
The structure of the data in a mixed database can be a barrier when clustering that database into me...
Distance measure plays an important role in clustering data points. Choosing the right distance meas...
One of the important aspects of panel data is the poolability of different units in the data set. Ho...
Distance metrics are broadly used in different research areas and applications, such as bio-informat...
<p>Hierarchical clustering was performed using Euclidean distance as a metric and using Ward method....
<p>Distance metrics are based on the Euclidean distance single linkage method (proximity matrix).</p
<p>To calculate the distances for the hierarchical and k-means clustering approaches, up to 7 mostly...
<p>The table represents the results of the three clustering measures (QLC, TE and HS) over 10 NJ rec...
The structure of the data in a mixed database can be a barrier when clustering that database into me...
Abstract. This paper introduces a hybrid hierarchical clustering method, which is a novel method for...
Abstract In this paper we suggest a new index for measuring the distance between two hierarchical cl...
<p>To calculate the pairwise distances for the hierarchical clustering, three commonly used linkage ...
Distance measures play an important role in cluster analysis. There is no single distance measure th...
Common goal of descriptive data mining techniques is presenting new information in concise, easily i...
Common goal of descriptive data mining techniques is presenting new information in concise, easily i...
The structure of the data in a mixed database can be a barrier when clustering that database into me...
Distance measure plays an important role in clustering data points. Choosing the right distance meas...
One of the important aspects of panel data is the poolability of different units in the data set. Ho...
Distance metrics are broadly used in different research areas and applications, such as bio-informat...
<p>Hierarchical clustering was performed using Euclidean distance as a metric and using Ward method....
<p>Distance metrics are based on the Euclidean distance single linkage method (proximity matrix).</p
<p>To calculate the distances for the hierarchical and k-means clustering approaches, up to 7 mostly...
<p>The table represents the results of the three clustering measures (QLC, TE and HS) over 10 NJ rec...
The structure of the data in a mixed database can be a barrier when clustering that database into me...
Abstract. This paper introduces a hybrid hierarchical clustering method, which is a novel method for...
Abstract In this paper we suggest a new index for measuring the distance between two hierarchical cl...
<p>To calculate the pairwise distances for the hierarchical clustering, three commonly used linkage ...