Perpustakaan Fakultas Ilmu Komputer

Pengarang	Daichi Ueki;
Judul Artikel	Principal points estimation using mizture distributions
Nama Prosiding	2012 International conference on advanced computer science and information systems (ICACSIS 2012) Depok, December 1st and 2nd 2012 Crystal of knowledge building Universitas Indonesia
Bahasa	eng
Abstrak English	The k-principal points of a distribution are the k points that optimally partition the distribution. In this paper, we propose a method to estimate principal points from data by using mixture distributions when we have no prior knowledge of the distribution of data. Several simulation results are presented to compare the proposed method with the nonparametric k-mean.
Tahun	2012
No. Panggil	SEM 304

Lokasi : Perpustakaan Fakultas Ilmu Komputer

Nomor Panggil	ID Koleksi	Status
SEM 304		TERSEDIA

Tidak ada review pada koleksi ini: 40385

The k-principal points of a distribution are the k points that optimally partition the distribution. In this paper, we propose a method to estimate principal points from data by using mixture distributions when we have no prior knowledge of the distribution of data. Several simulation results are presented to compare the proposed method with the nonparametric k-mean.