The file with product metadata have rows typically like these:
\n\n 49769 Sidral Mundet Lata 355ml CC 49769\n 49773 Bombonete San Valentin 3p 55g MLA 49773\n 49779 Tortillinas 22p 570g NW MTA TR 49779\nFirst question: I interpret this as "<name> <number of pieces> <volume/weight> <?> <ID>". I can't figure out the meaning of the characters CC, MLA, MTA etc. Any help to interpret this?
Second question: As stated in the goals, we are required to make predictions for products not in the training set. However, can we assume that any new product for which forecasting is needed, that we have the product metadata of the format above?
", "messages": [ { "id": "123741", "postDate": "06/13/2016 20:24:25", "content": "The file with product metadata have rows typically like these:
\n\n 49769 Sidral Mundet Lata 355ml CC 49769\n 49773 Bombonete San Valentin 3p 55g MLA 49773\n 49779 Tortillinas 22p 570g NW MTA TR 49779\nFirst question: I interpret this as "<name> <number of pieces> <volume/weight> <?> <ID>". I can't figure out the meaning of the characters CC, MLA, MTA etc. Any help to interpret this?
Second question: As stated in the goals, we are required to make predictions for products not in the training set. However, can we assume that any new product for which forecasting is needed, that we have the product metadata of the format above?
", "rawMarkdown": "The file with product metadata have rows typically like these:\r\n\r\n 49769 Sidral Mundet Lata 355ml CC 49769\r\n 49773 Bombonete San Valentin 3p 55g MLA 49773\r\n 49779 Tortillinas 22p 570g NW MTA TR 49779\r\n\r\n**First question:** I interpret this as \"`Hey
\n\nRelated to your first question. Many people are saying that the CC, MLA, etc.. are different brands. Actually if you google the first product, you will confirm that the CC means Coca-Cola. What I didnt get yet is: why are we predicting products that are not Bimbo´s products?
\n\nThe new products (products that do not appear in the training set) certainly will have the same format.
", "rawMarkdown": "Hey\r\n\r\nRelated to your first question. Many people are saying that the CC, MLA, etc.. are different brands. Actually if you google the first product, you will confirm that the CC means Coca-Cola. What I didnt get yet is: why are we predicting products that are not Bimbo´s products?\r\n\r\nThe new products (products that do not appear in the training set) certainly will have the same format.", "votes": null }, { "id": "123827", "postDate": "06/14/2016 04:16:35", "content": "Thanks for the info. Makes sense. Too bad though, since it precludes using that category to attempt to match a new product to an already characterized product class.
\n\nAnd yes, predicting so many other non-Bimbo products appears odd.
", "rawMarkdown": "Thanks for the info. Makes sense. Too bad though, since it precludes using that category to attempt to match a new product to an already characterized product class.\r\n\r\nAnd yes, predicting so many other non-Bimbo products appears odd.", "votes": null }, { "id": "123913", "postDate": "06/14/2016 13:12:35", "content": "Most of the products are Bimbo Brands, the other products are most likely products they distribute on the routes like CC, Coca Cola.
", "rawMarkdown": "Most of the products are Bimbo Brands, the other products are most likely products they distribute on the routes like CC, Coca Cola.", "votes": null }, { "id": "125259", "postDate": "06/28/2016 07:17:46", "content": "Some of the acronyms, immediately before the brand name, appear to be packaging types. But I cannot figure out what NW and MTA mean :-(
", "rawMarkdown": "Some of the acronyms, immediately before the brand name, appear to be packaging types. But I cannot figure out what NW and MTA mean :-(", "votes": null }, { "id": "125307", "postDate": "06/28/2016 14:17:36", "content": "what are the other ones, CU, TAB, TNB? I haven't been able to figure them out...
", "rawMarkdown": "what are the other ones, CU, TAB, TNB? I haven't been able to figure them out...", "votes": null }, { "id": "126434", "postDate": "07/08/2016 12:38:21", "content": "In this competition, you will forecast the demand of a product for a given week, at a particular store.\nHow is the store defined ???\nEvery week, there are delivery trucks that deliver products to the vendors. What does vendors mean in the scope of the problem.\nCliente_ID — Client ID ------->>>> is this vendor or store ???\ni am assuming that a client(Cliente_ID — Client ID) may have stores at different locations (Ruta_SAK — Route ID (Several routes = Sales Depot)).\nin this context what does---->>>> Agencia_ID — Sales Depot ID---->>>>Canal_ID — Sales Channel ID mean. I might look confused and really.............can someone explain thee relations between given variables.
", "rawMarkdown": "In this competition, you will forecast the demand of a product for a given week, at a particular store.\r\nHow is the store defined ???\r\nEvery week, there are delivery trucks that deliver products to the vendors. What does vendors mean in the scope of the problem.\r\nCliente_ID — Client ID ------->>>> is this vendor or store ???\r\ni am assuming that a client(Cliente_ID — Client ID) may have stores at different locations (Ruta_SAK — Route ID (Several routes = Sales Depot)).\r\nin this context what does---->>>> Agencia_ID — Sales Depot ID---->>>>Canal_ID — Sales Channel ID mean. I might look confused and really.............can someone explain thee relations between given variables.", "votes": null } ], "comments": [ { "id": 123788, "author_name": "caiotrucolo", "author_url": "", "post_date": "06/14/2016 00:58:41", "content": "Hey
\n\nRelated to your first question. Many people are saying that the CC, MLA, etc.. are different brands. Actually if you google the first product, you will confirm that the CC means Coca-Cola. What I didnt get yet is: why are we predicting products that are not Bimbo´s products?
\n\nThe new products (products that do not appear in the training set) certainly will have the same format.
", "votes": null, "replies": [] }, { "id": 123827, "author_name": "ajohrn", "author_url": "", "post_date": "06/14/2016 04:16:35", "content": "Thanks for the info. Makes sense. Too bad though, since it precludes using that category to attempt to match a new product to an already characterized product class.
\n\nAnd yes, predicting so many other non-Bimbo products appears odd.
", "votes": null, "replies": [] }, { "id": 123913, "author_name": "bengalstro", "author_url": "", "post_date": "06/14/2016 13:12:35", "content": "Most of the products are Bimbo Brands, the other products are most likely products they distribute on the routes like CC, Coca Cola.
", "votes": null, "replies": [] }, { "id": 125259, "author_name": "colinpriest", "author_url": "", "post_date": "06/28/2016 07:17:46", "content": "Some of the acronyms, immediately before the brand name, appear to be packaging types. But I cannot figure out what NW and MTA mean :-(
", "votes": null, "replies": [] }, { "id": 125307, "author_name": "bengalstro", "author_url": "", "post_date": "06/28/2016 14:17:36", "content": "what are the other ones, CU, TAB, TNB? I haven't been able to figure them out...
", "votes": null, "replies": [] }, { "id": 126434, "author_name": "bindukumar", "author_url": "", "post_date": "07/08/2016 12:38:21", "content": "In this competition, you will forecast the demand of a product for a given week, at a particular store.\nHow is the store defined ???\nEvery week, there are delivery trucks that deliver products to the vendors. What does vendors mean in the scope of the problem.\nCliente_ID — Client ID ------->>>> is this vendor or store ???\ni am assuming that a client(Cliente_ID — Client ID) may have stores at different locations (Ruta_SAK — Route ID (Several routes = Sales Depot)).\nin this context what does---->>>> Agencia_ID — Sales Depot ID---->>>>Canal_ID — Sales Channel ID mean. I might look confused and really.............can someone explain thee relations between given variables.
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "123741": "The file with product metadata have rows typically like these:\r\n\r\n 49769 Sidral Mundet Lata 355ml CC 49769\r\n 49773 Bombonete San Valentin 3p 55g MLA 49773\r\n 49779 Tortillinas 22p 570g NW MTA TR 49779\r\n\r\n**First question:** I interpret this as \"`