Hi Abijith.
It depends on how you want to interpret the strings.
If they are texts and you want to interpret them based on their content,
Brians suggestion is the right one.
If you want to consider each possible string as a distinct feature, the
OneHotEncoder would be the right choice.
Could you give an example of what the strings and the semantics of the
strings are?
Andy
On 06/20/2014 06:05 PM, Abijith Kp wrote:
Can anyone help me with the problem of dealing with feature which are
both strings of varying length(say from 0 to 100-150 characters) and
numbers?
What will be the most widely used techniques in such kind of
situations? And can it be solved using only scikit-learn?
PS: Initially I have to convert a json file to a feature's list, and
then use it.
Any help is appreciated.
Regards,
Abijith
--
Abijith KP
github.com/abijith-kp <http://github.com/abijith-kp>
kpabijith.wordpress.com <http://kpabijith.wordpress.com>
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Find What Matters Most in Your Big Data with HPCC Systems
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Leverages Graph Analysis for Fast Processing & Easy Data Exploration
http://p.sf.net/sfu/hpccsystems
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