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zn-CN: tutorials/estimators/boosted_trees.ipynb #906

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merged 6 commits into from Sep 13, 2019

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@Berrywrq
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commented Aug 5, 2019

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commented Aug 5, 2019

Preview and run these notebook edits with Google Colab:

Notebook diffs available on ReviewNB.com.

@googlebot googlebot added the cla: yes label Aug 5, 2019

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commented Aug 5, 2019

Reviewers added, please take a look.
@kuri-leo, @JayYip, @yantaozhao, @loveunk, @Wind2esg, @tigerneil, @MofiiTech, @gaoljhy, @Mr-Linus, @flopsySong, @echosun1996

When your review is finished, approve the pull request or include "LGTM" in your comment.

" <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/docs/blob/master/site/zh-cn/beta/tutorials/estimators/boosted_trees.ipynb\"><img src=\"https://tensorflow.google.cn/images/colab_logo_32px.png\" />在 Google Colab 中运行</a>\n",
" </td>\n",
" <td>\n",
" <a target=\"_blank\" href=\"https://github.com/tensorflow/docs/blob/master/site/zh-cn/beta/tutorials/estimators/boosted_trees.ipynb\"><img src=\"https://tensorflow.google.cn/images/GitHub-Mark-32px.png\">在 GitHub 上查看源代码b</a>\n",

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@Mr-Linus

Mr-Linus Aug 12, 2019

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" <a target=\"_blank\" href=\"https://github.com/tensorflow/docs/blob/master/site/zh-cn/beta/tutorials/estimators/boosted_trees.ipynb\"><img src=\"https://tensorflow.google.cn/images/GitHub-Mark-32px.png\">在 GitHub 上查看源代码b</a>\n",
" <a target=\"_blank\" href=\"https://github.com/tensorflow/docs/blob/master/site/zh-cn/beta/tutorials/estimators/boosted_trees.ipynb\"><img src=\"https://tensorflow.google.cn/images/GitHub-Mark-32px.png\">在 GitHub 上查看源代码</a>\n",
"id": "dW3r7qVxzqN5"
},
"source": [
"本教程是使用基于 `tf.estimator`API的决策树来训练梯度提升模型的端到端演示。提升树(Boosted Trees)模型是回归和分类问题中最受欢迎并最有效的机器学习方法之一。这是一种融合技术,它结合了几个(10 个,100 个或者甚至 1000 个)树模型的预测值。\n",

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@Mr-Linus

Mr-Linus Aug 12, 2019

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"本教程是使用基于 `tf.estimator`API的决策树来训练梯度提升模型的端到端演示。提升树(Boosted Trees)模型是回归和分类问题中最受欢迎并最有效的机器学习方法之一。这是一种融合技术,它结合了几个(10 个,100 个或者甚至 1000 个)树模型的预测值。\n",
"本教程是使用基于 `tf.estimator` API的决策树来训练梯度提升模型的端到端演示。提升树(Boosted Trees)模型是回归和分类问题中最受欢迎并最有效的机器学习方法之一。这是一种融合技术,它结合了几个(10 个,100 个或者甚至 1000 个)树模型的预测值。\n",
"# 构建一个拥有两个隐层,隐藏节点分别为 30 和 10 的深度神经网络。\n",
"classifier = tf.estimator.DNNClassifier(\n",
" feature_columns=my_feature_columns,\n",
" # 隐层所含结点数量分别为 30 和 10.\n",

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@Mr-Linus

Mr-Linus Aug 12, 2019

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" # 隐层所含结点数量分别为 30 和 10.\n",
" # 隐层所含结点数量分别为 30 和 10\n",

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@Berrywrq

Berrywrq Aug 21, 2019

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Thanks, I have made some modifications, please check

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LGTM

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Thanks. Some things have moved around as we switch the site to TF2-first. Can you rebase and make sure everything lines up with https://github.com/tensorflow/docs/tree/master/site/en/tutorials/estimator ?

These files should move to:

  • site/zh-cn/tutorials/estimator/boosted_trees.ipynb
  • site/zh-cn/tutorials/estimator/premade.ipynb

(and update links)

@lamberta lamberta added the invalid label Sep 9, 2019

Berrywrq and others added 6 commits Aug 5, 2019

@lamberta lamberta force-pushed the Berrywrq:boosted_tree branch from 5630db3 to a8209eb Sep 13, 2019

@lamberta lamberta removed the invalid label Sep 13, 2019

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Thanks for the translation and review 🚀

TensorFlow-Docs-Copybara pushed a commit that referenced this pull request Sep 13, 2019
Copybara-Service
Merge pull request #906 from Berrywrq:boosted_tree
PiperOrigin-RevId: 268995026

@TensorFlow-Docs-Copybara TensorFlow-Docs-Copybara merged commit a8209eb into tensorflow:master Sep 13, 2019

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