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標(biāo)題: Titlebook: Cluster Analysis; A Survey Patrick L. Odell,Benjamin S. Duran Book 1974 Springer-Verlag Berlin · Heidelberg 1974 Mathematica.algorithms.cal [打印本頁(yè)]

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書目名稱Cluster Analysis影響因子(影響力)




書目名稱Cluster Analysis影響因子(影響力)學(xué)科排名




書目名稱Cluster Analysis網(wǎng)絡(luò)公開度




書目名稱Cluster Analysis網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Cluster Analysis被引頻次




書目名稱Cluster Analysis被引頻次學(xué)科排名




書目名稱Cluster Analysis年度引用




書目名稱Cluster Analysis年度引用學(xué)科排名




書目名稱Cluster Analysis讀者反饋




書目名稱Cluster Analysis讀者反饋學(xué)科排名





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Applications,columns (numbers of resolution elements per scan line) of one resolution element (an individual). Each cell (individual, I) generates a p x 1 measurement vector X., i = 1, 2,…,r, and j = 1, 2,…,c. In order to recognize a scene, one must perform rc = n discriminate tasks “as effectively as possible”,
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Gesetzlich geschützte Lebensst?ttenr that a certain criterion of homogeneity within clusters is satisfied. A way of accomplishing this objective as discussed in Chapter 2 is by complete enumeration, i.e., examine the homogeneity criterion for all possible partitions into m clusters and choose that one which is optimal. Unfortunately,
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978-3-540-06954-6Springer-Verlag Berlin · Heidelberg 1974
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Lecture Notes in Economics and Mathematical Systemshttp://image.papertrans.cn/c/image/228526.jpg
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The Cluster Problem and Preliminary Ideas,avoid specialization to perhaps a few fields of application we will discuss the technique from a general and perhaps somewhat abstract approach in this chapter and give what we consider interesting applications in a later chapter.
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Applications,columns (numbers of resolution elements per scan line) of one resolution element (an individual). Each cell (individual, I) generates a p x 1 measurement vector X., i = 1, 2,…,r, and j = 1, 2,…,c. In order to recognize a scene, one must perform rc = n discriminate tasks “as effectively as possible”, (if the scene is classified point by point).
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Historical Comments, publications dealing with cluster analysis have occurred in a wide variety of journals which treat a diversity of topics. Consequently, a work which unifies the various results and presents them in a coherent fashion is lacking. The first six chapters (with the possible exception of chapter 2) have been an attempt to do this.
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Cluster Analysis978-3-642-46309-9Series ISSN 0075-8442 Series E-ISSN 2196-9957
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https://doi.org/10.1007/978-3-540-69097-9columns (numbers of resolution elements per scan line) of one resolution element (an individual). Each cell (individual, I) generates a p x 1 measurement vector X., i = 1, 2,…,r, and j = 1, 2,…,c. In order to recognize a scene, one must perform rc = n discriminate tasks “as effectively as possible”, (if the scene is classified point by point).
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0075-8442 references to papers in applied journals are also contained, however, the list-is far from being complete. This monograph has been greatly influenced by the wor978-3-540-06954-6978-3-642-46309-9Series ISSN 0075-8442 Series E-ISSN 2196-9957
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Gesetzlich geschützte Lebensst?tten is a Stirling’s number of the second kind and can be computed by means of a formula to be derived in the next section. This chapter is only incidently related to the cluster problem and may be omitted by the reader.
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0075-8442 substantial portion of this work has appeared in many journals, including numerous applied journals, and a unified ex- position is lacking. The purpose of this monograph is to supply such an exposition by presenting a brief survey on cluster analysis. The main intent of the monograph is to give the
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