直接在R中实施自定义停止指标以在H2O模型训练期间进行优化 [英] Implementing custom stopping metrics to optimize during training in H2O model directly from R

问题描述

我正在尝试实现 FBeta_Score() MLmetrics R包:

FBeta_Score <- function(y_true, y_pred, positive = NULL, beta = 1) {
   Confusion_DF <- ConfusionDF(y_pred, y_true)
   if (is.null(positive) == TRUE) 
   positive <- as.character(Confusion_DF[1,1])
   Precision <- Precision(y_true, y_pred, positive)
   Recall <- Recall(y_true, y_pred, positive)
   Fbeta_Score <- (1 + beta^2) * (Precision * Recall) / (beta^2 * Precision + 
   Recall)
   return(Fbeta_Score)
 }

在 H2O分布式随机森林模型中，，我想在培训阶段使用custom_metric_func选项对其进行优化. h2o.randomForest()函数的帮助文档说:

in the H2O distributed random forest model and I want to optimize it during the training phase using the custom_metric_func option. The help documentation of the h2o.randomForest() function says:

自定义评估功能的参考，格式: 'language:keyName = funcName'

Reference to custom evaluation function, format: 'language:keyName=funcName'

但是我不明白如何直接从R中使用它，以及我应该在stopping_metric选项中指定的内容.

But I don't understand how to use it directly from R and what I should specify in the stopping_metric option.

任何帮助将不胜感激！

推荐答案

当前仅对基于Python的自定义函数提供后端支持，可以通过

Currently there is only backend support for Python-based custom functions, which can be uploaded to the backend via the h2o.upload_custom_metric() function. This function will then return a function reference (this is a string that has a naming convention format of 'language:keyName=funcName'). That you can then pass to the custom_metric parameter.

例如:

custom_mm_func = h2o.upload_custom_metric(CustomRmseFunc, func_name="rmse", func_file="mm_rmse.py")

返回具有以下值的函数引用:

returns a function reference which has the following value:

> print(custom_mm_func)
python:rmse=mm_rmse.CustomRmseFuncWrapper

关于将自定义指标用作停止指标的第二个问题，您可以在此处找到一张吉拉票: https://0xdata.atlassian.net/browse/PUBDEV-5261

As for your second question about using the custom metric as a stopping metric, there is a jira ticket that you can follow here: https://0xdata.atlassian.net/browse/PUBDEV-5261

您可以找到有关如何使用自定义指标的更多详细信息此处.

You can find more details on how to use the custom metric here.

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