Traditional instruction dramatically underestimates the percentage of self-starters whose boundless curiosity has no need for authoritarian direction.

传统的教学大大低估了自学者的比例，这些自学者的无穷的好奇心使他们根本不需要老师的指导。

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To facilitate clustering analysis and visualization of data, the Emergent Self-Organizing Feature Maps (ESOM) and a boundless U-matrix are needed.

本文通过利用涌现自组织特征映射神经网络对数据进行聚类分析，并通过无边界u矩阵实现可视化功能。

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