Dear Mahout Team,
I am a student new to machine learning and i am trying to build a user
based recommender using mahout.
My dataset is a csv file as an input but it has many fields as text and i
understand mahout needs numeric values.
Can you give me a headstart as to where i should start and wh
Hello Yash,
checkout the following project:
https://github.com/ManuelB/facebook-recommender-demo
/Manuel
--
Manuel Blechschmidt
Mobil: +49 (0) 173 6322621
Ursprüngliche Nachricht Von: Yash Patel
Datum:26.11.2014 20:16 (GMT+01:00)
An: user@mahout.apache.org Betreff: User b
kindly elaborate... your requirements... your dataset fields ...and what
you want to recommend to an user... Usually a set of item is recommended to
an user. In your case what are your items ?
The standard input is . Clearly your data is not
in this format which will let you use directly the algo
Hi Yash,
What exactly do you mean by “user-based” recommender? What does your data look
like? What are the columns in the CSV? For collaborative filtering you will
need a user-ID and an item-ID for each preference the user has expressed.
Mahout has several recommenders so building one should
All very good points but note that spark-itemsimilarity may take the input
directly since you specify column numbers for
On Nov 26, 2014, at 11:43 AM, parnab kumar wrote:
kindly elaborate... your requirements... your dataset fields ...and what
you want to recommend to an user... Usually a set
Hello everyone,
wow i am quite happy to see so many inputs from people.
I apologize for not providing more details.
Although this is not my complete dataset the fields i have chosen to use
are:
customer id - numeric
item id - text
postal code - text
item category ´- text
potential growth - text
