Supervised and unsupervised approaches for classification of remote sensing data by computer are discussed. Some primary classification results are provided.

讨论了遥感数据监督指非监督和计算机自动分类的问题，并给出了一些初步的分类结果实例。

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Its effectiveness has been testified by computer simulating experiment and it can be regarded as a promising machine learning for the pattern classification system.

该算法的有效性已由计算机仿真实验所证实，可被认为是一种很有发展前途的模式分类系统的机器学习算法。

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Methods we studied and analysed by the method of incidence analysis and the ICD disease classification, wherein data were collected via the computer.

方法采用灰色关联度分析法和I CD国际疾病分类进行微机汇总库调研。

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