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对比sklearn：gamma的取值问题 #6

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oahcnauygnid opened this issue Mar 28, 2023 · 0 comments

oahcnauygnid commented Mar 28, 2023 •

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在sklearn里对gamma的描述是使用X.var()

gamma : {'scale', 'auto'} or float, default='scale'
        Kernel coefficient for 'rbf', 'poly' and 'sigmoid'.

        - if ``gamma='scale'`` (default) is passed then it uses
          1 / (n_features * X.var()) as value of gamma,
        - if 'auto', uses 1 / n_features.

但目前这里用的是X.std()，

kernel_func = self.register_kernel(X.std())

导致收敛速度很慢，但确实取得了更高的准确度，这是有什么考量吗？

对比大概是
sklearn 时间0.004s 准确度0.9035
X.var()+1阶时间2.7s 准确度0.9035
X.var()+2阶时间18s 准确度0.9035
X.std()+1阶时间15s 准确度0.9649
X.std()+2阶时间25s 准确度0.9649

oahcnauygnid changed the title ~~gamma的取值问题~~ 对比sklearn：gamma的取值问题

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