Add to ORKGRomano E., Giordano G., Lauro C. N. (2006), "An inter-models distance for clustering utility functions", Statistica Applicata - Italian Journal of Applied Statistics, Vol. 17, n. 2
Mahalanobis-type distances in which the shape matrix is derived from a consistent highbreakdown robu...
Outlier detection is a fundamental issue in data mining, specifically it has been used to detect and...
In this paper, we present our research on data mining approaches with the existence of obstacles. Al...
In recent years curve clustering problem has been handled in several applicative fields. However, mo...
Outliers are eccentric data points with anomalous nature. Clustering with outliers has received a lo...
A novel approach to outlier detection and clustering on the ground of the distribution of distances ...
Conjoint Analysis is one of the most widely used techniques in the assessment of the consumer’s beha...
"A two-phase clustering method for the detection of geostatistical functional. outliers is proposed....
Classification is a very common task in information processing and important problem in many sectors...
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Man...
Cluster analysis is a popular unsupervised learning method. Its goal is to find a partition of a dat...
A discrete space-filling curve provides a linear traversal/indexing of a multi-dimensional grid spac...
Recent developments in local search analysis have yielded the first polynomial-time approximation sc...
none1noThe paper presents a selective view of the issues that are attracting the interest of Italian...
Outlier detection is a fundamental issue in data mining, specifically it has been used to detect and...
Mahalanobis-type distances in which the shape matrix is derived from a consistent highbreakdown robu...
Outlier detection is a fundamental issue in data mining, specifically it has been used to detect and...
In this paper, we present our research on data mining approaches with the existence of obstacles. Al...
In recent years curve clustering problem has been handled in several applicative fields. However, mo...
Outliers are eccentric data points with anomalous nature. Clustering with outliers has received a lo...
A novel approach to outlier detection and clustering on the ground of the distribution of distances ...
Conjoint Analysis is one of the most widely used techniques in the assessment of the consumer’s beha...
"A two-phase clustering method for the detection of geostatistical functional. outliers is proposed....
Classification is a very common task in information processing and important problem in many sectors...
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Man...
Cluster analysis is a popular unsupervised learning method. Its goal is to find a partition of a dat...
A discrete space-filling curve provides a linear traversal/indexing of a multi-dimensional grid spac...
Recent developments in local search analysis have yielded the first polynomial-time approximation sc...
none1noThe paper presents a selective view of the issues that are attracting the interest of Italian...
Outlier detection is a fundamental issue in data mining, specifically it has been used to detect and...
Mahalanobis-type distances in which the shape matrix is derived from a consistent highbreakdown robu...
Outlier detection is a fundamental issue in data mining, specifically it has been used to detect and...
In this paper, we present our research on data mining approaches with the existence of obstacles. Al...