Kaggle Project - Predict Future Sales

0 . Predict Future Sales  

- 캐글 링크 

불러오는 중입니다...

 

1. Data Description

- 일일 이력 판매 데이터가 제공됩니다. 작업은 테스트 세트에 대해 모든 상점에서 판매 된 총 제품 수를 예측하는 것입니다. 상점 및 제품 목록은 매달 약간 씩 변경됩니다. 이러한 상황을 처리 할 수있는 강력한 모델을 만드는 것은 어려운 일 중 하나입니다.

 

<File descriptions>

 

• sales_train.csv - the training set. Daily historical data from January 2013 to October 2015.

• test.csv - the test set. You need to forecast the sales for these shops and products for November 2015.

• sample_submission.csv - a sample submission file in the correct format.

• items.csv - supplemental information about the items/products.

• item_categories.csv  - supplemental information about the items categories.

• shops.csv- supplemental information about the shops.

 

 

<Data fileds> 

• ID - an Id that represents a (Shop, Item) tuple within the test set
• shop_id - unique identifier of a shop
• item_id - unique identifier of a product
• item_category_id - unique identifier of item category
• item_cnt_day - number of products sold. You are predicting a monthly amount of this measure
• item_price - current price of an item
• date - date in format dd/mm/yyyy
• date_block_num - a consecutive month number, used for convenience. January 2013 is 0, February 2013 is 1,..., October 2015 is 33
• item_name - name of item
• shop_name - name of shop
• item_category_name - name of item category

 

2. 참고 이론