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- Basic_sequential_algorithmic_scheme abstract "The basic sequential algorithmic scheme (BSAS) is a very basic clustering algorithm that is easy to understand. In the basic form vectors are presented only once and the number of clusters is not known a priori. What is needed is the dissimilarity measured(x, C), threshold of dissimilarity Θ and the number of maximum clusters allowed g.The idea is to assign every newly presented vector to an existing cluster or create a newcluster for this sample, depending on the distance to the already defined clusters. Aspseudo the algorithm works like the following: 1. m = 1; Cm = {x1}; // Init first cluster = first sample 2. for every sample x from 2 to N a. find cluster Ck such that min d(x, Ck) b. if d(x, Ck) > Θ AND (m < q) i. m = m + 1; Cm = {x} // Create a new cluster c. else i. Ck = Ck + {x} // Add sample to the nearest cluster ii. Update representative if needed 3. end algorithmAs can be seen the algorithm is simple but still quite efficient. Different choices for the distance function lead to different results and unfortunately the order in which the samples are presented can also have a great effect to the final result. What’s also very important is a correct value for Θ. This value has a direct effect on the number of formed clusters. If Θ is too small unnecessary clusters are created and if too large a value is chosen less than required number of clusters are formed.One detail is that if q is not defined the algorithm ‘decides’ the number of clusters on its own. This might be wanted under some circumstances but when dealing with limited resources a limited q is usually chosen. Also, it should be noted that BSAS can be used with a similarity function simply by replacing the min function with max.There exists a modification to BSAS called modified BSAS (MBSAS), which runs twice through the samples. It overcomes the drawback that a final cluster for a single sample is decided before all the clusters have been created. The first phase of the algorithm creates the clusters (just like 2b in BSAS) and assigns only a single sample to each cluster. Then the second phase runs through the remaining samples and classifies them to the created clusters (step 2c in BSAS).".
- Basic_sequential_algorithmic_scheme wikiPageExternalLink clustering.pdf.
- Basic_sequential_algorithmic_scheme wikiPageExternalLink PR08.pdf.
- Basic_sequential_algorithmic_scheme wikiPageID "41948842".
- Basic_sequential_algorithmic_scheme wikiPageRevisionID "601335551".
- Basic_sequential_algorithmic_scheme subject Category:Data_clustering_algorithms.
- Basic_sequential_algorithmic_scheme comment "The basic sequential algorithmic scheme (BSAS) is a very basic clustering algorithm that is easy to understand. In the basic form vectors are presented only once and the number of clusters is not known a priori.".
- Basic_sequential_algorithmic_scheme label "Basic sequential algorithmic scheme".
- Basic_sequential_algorithmic_scheme sameAs m.0_qldgk.
- Basic_sequential_algorithmic_scheme sameAs Q16251193.
- Basic_sequential_algorithmic_scheme sameAs Q16251193.
- Basic_sequential_algorithmic_scheme wasDerivedFrom Basic_sequential_algorithmic_scheme?oldid=601335551.
- Basic_sequential_algorithmic_scheme isPrimaryTopicOf Basic_sequential_algorithmic_scheme.