ML_Scaling to Huge Datasets & Online Learning

比对梯度下降和随机梯度下降:

梯度下降:每一次迭代耗时长,在大数据集上处理速度慢,对参数敏感性适中

随机梯度下降:每一次迭代耗时短,在大数据集上处理速度较快,但对参数非常敏感

随机梯度下降能更快地达到较大的对数似然值,但噪声更大

步长太小,收敛速度太慢;步长较大,震荡较大;步长异常大,不收敛

时间: 2024-08-07 04:33:35

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