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# System prepended metadata

title: 討論區要求與模板 Discussion Forum Requirements and Template
tags: [course]

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# 討論區要求與模板 Discussion Forum Requirements and Template
###### tags: `course`
---

You can edit the page simply by clicking on the top-right button <i class="fa fa-pencil"></i> and the top-left bottom  <i class="fa fa-columns"></i>.

(按右上方<i class="fa fa-pencil"></i> 之後再按左上方<i class="fa fa-columns"></i>，即可編輯本頁)

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### 討論區要求 Requirments: 
    * Please follow the following templates
    * Please do not insert photos
    * You are encouraged to answer other's questions
    * Try your best to use English in Hands-on sections

### 模板 Templates

> 教科書是否能團購呢?
>> 請同學自己揪團喔
>> [name=Joy][color=#42ffe8]

>  Can someone illustrate cross validation. We are discussing with our group.
We think cross validation partitions the Z training set into n z training sets. Say for Decision trees, does it mean that we generate n trees and we pick the one with best accuracy on the test data?
More insight and clarification about cross validation would be appreciated
>> Let's use decision trees as an example, where n=5 folds. We would first train 5 separate decision trees, where each fold has a turn being the validation data and the rest of the data is the training set ... 
>> This video might help: 
>> [](https://)https://www.youtube.com/watch?v=OwPQHmiJURI.
>> [name=TA][color=#42ffe8]
>> 

