# CS98X-DL-Task2-Contract-Clasification — Data

来源：https://www.kaggle.com/competitions/cs98x-dl-task2-contract-clasification/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

<p>Below are the descriptions of the training and test data. Your task is to predict the field called "label" which is a binary string that represents the 9 classes: "General", "Defence", "Education & Culture", "Energy & Environment"," Health & Care", "Infrastructure & Construction", "Professional Services", "Technology & Communications", "Transport & Logistics".</p>

<p>The training data contain the classes in a field called "category"- but the test data does not!</p>


<h2>File descriptions</h2>
<ul>
<li><strong>contacts-train.csv</strong> - the training set</li>
<li><strong>contracts-test.csv</strong> - the test set</li>
<li><strong>contracts-sample-submission_1.csv</strong> - a sample submission file in the correct format</li>
</ul>
<h2>Data fields</h2>
<ul>
<li>'publication_date' - the date the contract was published</li>
<li>'contract_type' - notice or award</li>
 <li>'nature_of_contract' - supplies, works, or services</li>
 <li>'country_code' - two letter to represent the country that issued the tender</li>
<li>'country_name' - country name </li>
<li>'sector' - private or public sector tender</li>
<li>'category' - a list of the categories the contract belongs
<li>'value' - value of the tender, if available</li>
'<li>title' - title of the tender</li>
<li>'description’- description of the tender</li>
<li>'awarding_authority' - authority that will award the contract</li>
<li>'complete_entry' - the complete text associated with the tender</li>

<li>'label' - the classes that the document belongs to (given fields, "General", "Defence","Education & Culture","Energy & Environment","Health & Care","Infrastructure & Construction","Professional Services","Technology & Communications","Transport & Logistics”</li>
</ul>