Simulation results show that the algorithm can achieve more stable clustering accuracy on the benchmark data sets.
实验结果显示,该算法在不同结构和维数的数据集上都取得了更稳定的聚类精度。
Your hardware vendor should have benchmark data stating the expected Memory, CPU (FLOPS), Disk, and Network performance.
硬件厂商应该有基准测试数据,这些数据说明预期的内存、CPU (FLOPS)、磁盘和网络性能。
Although this is a sizing example, IBM sizing tools rely not only on the derived benchmark data, but also on analysis and feedback from both customer and internal production environments.
虽然这是一个分级示例,但IBM分级工具不仅依赖于派生的基准数据,还依赖于来自客户和内部生产环境的分析和反馈。
Here's ten years worth of data from the Frank Russell Corporation, the benchmark Wilshire 5000.
这是来自罗素公司的,十年数据,道琼斯威尔希尔5000指数
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