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K-means clustering
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Bài giảng Khai phá dữ liệu (Data mining): Clustering, chương này trình bày những nội dung về: giới thiệu Clustering; phân loại; thuật toán Kmeans; hierarchical clustering; density-based clustering; bài tập;... Mời các bạn cùng tham khảo chi tiết nội dung bài giảng!
70p
diepkhinhchau
18-09-2023
12
6
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Bài giảng "Máy học nâng cao: Clustering" cung cấp cho người học các kiến thức: Giới thiệu - clustering, phân loại, thuật toán kmeans, hierarchical clustering, density based clustering. Cuối bài giảng có phần bài tập để người học ôn tập và củng cố kiến thức.
70p
abcxyz123_08
11-04-2020
46
4
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In this paper, we propose a two-phase educational data clustering method using transfer learning and kernel k-means algorithms for the student data clustering task on a small target data set from a target program while a larger source data set from another source program is available.
14p
vishizuka2711
07-04-2020
37
2
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So we are proposed Enhanced architecture with improved kmeans algorithm, which proposes a method for making the algorithm more effective and efficient, so as to get better clustering with reduced complexity. It will search the base keyword of the content from the knowledge database. Proposed work uses the search engine based on clustering and text mining.
6p
hongnhan878
12-04-2019
25
1
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This paper aimed to evaluate the impact of Euclidean and Manhattan distance metrics on Kmeans algorithm using for clustering KDD cup99 intrusion detection data. Experimental results indicate that Manhattan distance metric performs better in terms of performance evaluation metrics than Euclidean distance metric.
4p
byphasse043256
23-03-2019
32
1
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In this paper an approach to Content Based Image Retrieval (CBIR) is examined that uses Kmeans clustering for segmenting an image and then extracts global and local features using color and shape information over the extracted regions to compute a similarity measure between images.
8p
cumeo2005
02-07-2018
35
1
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The paper describes the application of kMeans, a standard clustering technique, to the task of inducing semantic classes for German verbs. Using probability distributions over verb subcategorisation frames, we obtained an intuitively plausible clustering of 57 verbs into 14 classes. The automatic clustering was evaluated against independently motivated, handconstructed semantic verb classes.
8p
bunmoc_1
20-04-2013
28
1
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