From 53475341fec0167cac27f92e0c850125b2651bdf Mon Sep 17 00:00:00 2001 From: Zebin YANG Date: Wed, 17 May 2023 16:48:36 +0800 Subject: [PATCH] Update --- docs/_build/html/_sources/guides/data/data_prepare.rst.txt | 5 ----- docs/_build/html/_sources/guides/data/data_summary.rst.txt | 2 -- docs/_build/html/guides/data/data_prepare.html | 4 ---- docs/_build/html/guides/data/data_summary.html | 1 - 4 files changed, 12 deletions(-) diff --git a/docs/_build/html/_sources/guides/data/data_prepare.rst.txt b/docs/_build/html/_sources/guides/data/data_prepare.rst.txt index c8666c10..bd3fd7f4 100644 --- a/docs/_build/html/_sources/guides/data/data_prepare.rst.txt +++ b/docs/_build/html/_sources/guides/data/data_prepare.rst.txt @@ -8,11 +8,6 @@ Data Preparation ====================================== -In this section, I will introduce the data preparation module of PiML. In data preparing function, you are allowed -to set the detailed config of the model training procedure, including task configs like target variable, task type, and sample_weight. -And there is the data split setting such as split method, split ratio, and random seed in the data preparing setting to decide how to split data for the experiment. -Besides the setting, you can also get train test data distance results. - This section introduces the data preparation module of PiML. In this function, you can set the detailed configuration of the model training procedure, including task configurations like target variable, task type, and sample_weight. Further, there is the data split setting such as split method, split ratio, and random seed to decide how to split data for the experiment. Besides the setting, you can also get results on the distances between train test datasets. diff --git a/docs/_build/html/_sources/guides/data/data_summary.rst.txt b/docs/_build/html/_sources/guides/data/data_summary.rst.txt index 07273ac6..e42e796b 100644 --- a/docs/_build/html/_sources/guides/data/data_summary.rst.txt +++ b/docs/_build/html/_sources/guides/data/data_summary.rst.txt @@ -7,8 +7,6 @@ ========================== Data Summary ========================== -This functionality summarizes basic data statistics and sets the meta information for the features. In this function, you can get the summary information of data based on its data type and also change the feature type and remove features. - Data summary is the process to summarize basic data statistics and setting the meta info of features. In this function, you could not only get the summary information of data based on its data type, but also you can change the feature type and remove features. diff --git a/docs/_build/html/guides/data/data_prepare.html b/docs/_build/html/guides/data/data_prepare.html index 1a1cfbde..6cef959e 100644 --- a/docs/_build/html/guides/data/data_prepare.html +++ b/docs/_build/html/guides/data/data_prepare.html @@ -248,10 +248,6 @@

2.3. Data Preparation

-

In this section, I will introduce the data preparation module of PiML. In data preparing function, you are allowed -to set the detailed config of the model training procedure, including task configs like target variable, task type, and sample_weight. -And there is the data split setting such as split method, split ratio, and random seed in the data preparing setting to decide how to split data for the experiment. -Besides the setting, you can also get train test data distance results.

This section introduces the data preparation module of PiML. In this function, you can set the detailed configuration of the model training procedure, including task configurations like target variable, task type, and sample_weight. Further, there is the data split setting such as split method, split ratio, and random seed to decide how to split data for the experiment. Besides the setting, you can also get results on the distances between train test datasets.

2.3.1. Setting

diff --git a/docs/_build/html/guides/data/data_summary.html b/docs/_build/html/guides/data/data_summary.html index b2649cca..b7a5c4ae 100644 --- a/docs/_build/html/guides/data/data_summary.html +++ b/docs/_build/html/guides/data/data_summary.html @@ -246,7 +246,6 @@

2.2. Data Summary

-

This functionality summarizes basic data statistics and sets the meta information for the features. In this function, you can get the summary information of data based on its data type and also change the feature type and remove features.

Data summary is the process to summarize basic data statistics and setting the meta info of features. In this function, you could not only get the summary information of data based on its data type, but also you can change the feature type and remove features.