成像侦察任务聚类是提高成像侦察卫星利用效率的重要手段。
Clustering imaging reconnaissance tasks is a significant way to improve imaging reconnaissance satellite's utilizable efficiency.
通过评价在两个消歧任务上的聚类结果，你需要探讨不同表示方法的优点并研究学习方法的性质。
By evaluating the resultant clustering on two disambiguation tasks, you will explore the merits of different representations and study the properties of the learning method.
我将使用最根本、最重要的查询和聚类算法，进行许多先进的任务，举例来说明我们如何解决这些问题。
I will use query and clustering, which are of fundamental importance to many advanced tasks, as examples to illustrate how we address these issues.
数据挖掘的任务有关联分析、时序模式、聚类、分类与预测等。
The tasks of data mining include association rules analysis, time series module, cluster analysis, classification and predication and so on.
聚类分析是数据挖掘中一种重要的挖掘任务和挖掘方法，使得聚类算法的效率和聚类质量在数据挖掘中起着至关重要的作用，也成了计算机科学领域的难题之一。
As an importance task and method for Data Mining, clustering analysis has a great impact on algorithmic efficiency and clustering quality, which is one of difficult problems in Computer Science area.
这是一个科学计算库，支持多维数组和线性代数数，在某些计算概率、标记、聚类和分类任务中用到。
This is a scientific computing library with support for multidimensional arrays and linear algebra, required for certain probability, tagging, clustering, and classification tasks.
聚类是多媒体数据挖掘的重要任务之一，数据之间的相似性度量是聚类的基础和前提。
Clustering is one of the focused problems in multimedia data mining, and similarity measurement among data is fundamental to clustering.
为了寻找与当前用户相似的顾客，聚类模型对顾客基础进行细分，并把这个任务当做为分类问题。
To find customers who are similar to the user, cluster models divide the customer base into many segments and treat the task as a classification problem.
从本质上讲，纹理聚类的任务是根据图像中各像素所处的不同区域，将它们归至未知的不同类别。
In essence, texture clustering is equal to classify different texture pictures to unknown classes on basis of pixels of an image belonging to different regions.
而模糊聚类算法则准确地完成对样本的分类任务。
Fuzzy clustering algorithm was used to classify the faults samples correctly.
基于颜色特征的图像分类，聚类及可视化等任务此时可在减少集上完成。
Original color-based tasks such as classification, clustering and visualization on image set can be then implemented on the reduced set.
基于颜色特征的图像分类，聚类及可视化等任务此时可在减少集上完成。
Original color-based tasks such as classification, clustering and visualization on image set can be then implemented on the reduced set.
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