我在Jupyter notebook中运行california测试代码，出现了很多lgbm的logging，我不想看到这些输出，我用了常规方法（import logging）没能解决，特来请教，logging如下示例：
[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000082 seconds.
You can set force_col_wise=true to remove the overhead.[LightGBM] [Info] Total Bins 255
[LightGBM] [Info] Total Bins 255
[LightGBM] [Info] Number of data points in the train set: 7231, number of used features: 1[LightGBM] [Info] Number of data points in the train set: 7231, number of used features: 1
[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000084 seconds.
You can set force_col_wise=true to remove the overhead.
[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000086 seconds.
You can set force_col_wise=true to remove the overhead.[LightGBM] [Info] Total Bins 255
[LightGBM] [Info] Total Bins 255[LightGBM] [Info] Number of data points in the train set: 7231, number of used features: 1[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000081 seconds.
You can set force_col_wise=true to remove the overhead.[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000082 seconds.
You can set force_col_wise=true to remove the overhead.
cslzh404
commented
1 year ago
我在Jupyter notebook中运行california测试代码，出现了很多lgbm的logging，我不想看到这些输出，我用了常规方法（import logging）没能解决，特来请教，logging如下示例： [LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000082 seconds. You can set
force_col_wise=trueto remove the overhead.[LightGBM] [Info] Total Bins 255[LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 7231, number of used features: 1[LightGBM] [Info] Number of data points in the train set: 7231, number of used features: 1
[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000084 seconds. You can set
force_col_wise=trueto remove the overhead. [LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000086 seconds. You can setforce_col_wise=trueto remove the overhead.[LightGBM] [Info] Total Bins 255[LightGBM] [Info] Total Bins 255[LightGBM] [Info] Number of data points in the train set: 7231, number of used features: 1[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000081 seconds. You can set
force_col_wise=trueto remove the overhead.[LightGBM] [Warning] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000082 seconds. You can setforce_col_wise=trueto remove the overhead.