Kontakt
Wie einkaufen
Versand
Kaufberater
High-Dimensional Data Mining
Subspace Clustering, Outlier Detection and applications to classification
Englisch
152 b
30 Tage für die Rückgabe der Ware
Kunden kauften auch
/
Broschur
10.29
€
/
Broschur
73.59
€
/
Broschur
19.99
€
Data mining in high dimensionality typically faces the consequences of increasing sparsity and declining differentiation between points, while sparsity tends to increase false negatives. Here, the problem of solving high-dimensional problems using low-dimensional solutions is addressed. In clustering, we provide a new framework for finding candidate subspaces and the clusters within them using only two-dimensional clustering. It is robust to noise and handles overlapping clusters. In the field of outlier detection, several novel algorithms suited to high-dimensional data are presented.m These outperform state-of-the-art outlier detection algorithms in ranking outlierness for many datasets regardless of whether they contain rare classes or not. This approach can be a powerful means of classification for heavily overlapping classes given sufficiently high dimensionality. This is achieved solely due to the differences in variance among the classes. On some difficult datasets, this unsupervised approach yielded better separation than the very best supervised classifiers. This opens a new field in data mining, classification through differences in variance rather than spatial location.
Informationen zum Buch
Englisch
Verschenken Sie dieses Buch noch heute
Es ist ganz einfach
1 Legen Sie das Buch in Ihren Warenkorb und wählen Sie den Versand als Geschenk 2 Wir schicken Ihnen umgehend einen Gutschein 3 Das Buch wird an die Adresse des beschenkten Empfängers geliefertDas könnte Sie auch interessieren
/
Broschur
83.09
€
/
Broschur
17.89
€
/
Broschur
13.59
€
