A notion of stability for k-means clustering
نویسندگان
چکیده
In this paper, we define and study a new notion of stability for the k-means clustering scheme building upon the field of quantization of a probability measure. We connect this definition of stability to a geometric feature of the underlying distribution of the data, named absolute margin condition, inspired by recent works on the subject.
منابع مشابه
خوشه‌بندی استان‌های ایران بر پایه‌ی معیارهای شکاف دیجیتال به کمک روش K-MEANS
In this paper, the notion of the digital divide has been described, and a few analyzing methods of digital divide have been reviewed. Analyzing methods of digital divide are called indices which have different indicators and different formulas for calculation. Since data collection for an indicator may be difficult, calculating an index is an essential problem. We collected and calculated some ...
متن کاملPersistent K-Means: Stable Data Clustering Algorithm Based on K-Means Algorithm
Identifying clusters or clustering is an important aspect of data analysis. It is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. It is a main task of exploratory data mining, and a common technique for statistical data analysis This paper proposed an improved version of K-Means algorithm, namely Persistent K...
متن کاملModification of the Fast Global K-means Using a Fuzzy Relation with Application in Microarray Data Analysis
Recognizing genes with distinctive expression levels can help in prevention, diagnosis and treatment of the diseases at the genomic level. In this paper, fast Global k-means (fast GKM) is developed for clustering the gene expression datasets. Fast GKM is a significant improvement of the k-means clustering method. It is an incremental clustering method which starts with one cluster. Iteratively ...
متن کاملImproved COA with Chaotic Initialization and Intelligent Migration for Data Clustering
A well-known clustering algorithm is K-means. This algorithm, besides advantages such as high speed and ease of employment, suffers from the problem of local optima. In order to overcome this problem, a lot of studies have been done in clustering. This paper presents a hybrid Extended Cuckoo Optimization Algorithm (ECOA) and K-means (K), which is called ECOA-K. The COA algorithm has advantages ...
متن کاملGROUND MOTION CLUSTERING BY A HYBRID K-MEANS AND COLLIDING BODIES OPTIMIZATION
Stochastic nature of earthquake has raised a challenge for engineers to choose which record for their analyses. Clustering is offered as a solution for such a data mining problem to automatically distinguish between ground motion records based on similarities in the corresponding seismic attributes. The present work formulates an optimization problem to seek for the best clustering measures. In...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- CoRR
دوره abs/1801.09419 شماره
صفحات -
تاریخ انتشار 2018