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On 1/10/13 11:14 AM, Walshe, Maurice (RBIUK) wrote:
> unsubscribe
>
> Original Message
> From: akshay shetye [mailto:akshay.shetye@gmail.com]
> Sent: 10 January 2013 14:40
> To: user@mahout.apache.org
> Subject: Re: machine learning algorithm giving wrong results
>
> Thanks for replying.This is not a homework problem ,I just related my
> real use case to a simple example problem.
>
> I did regression and problem i was facing is i get negative predictions
> of travel time.
> There are many other features in input feature list , Day of week : (on
> some days he goes to church /temple on the way) Start time : (there will
> be more traffice at 8.30 than 7) etc
>
> Can u elaborate more and tell about the solution.Am not a expert in
> machine learning . am new to this.
>
> Note :sorry for starting new thread i somehow dont get mails of this
> user group in this mail Regards, Damodar
>
>  This is a regression problem. The regression algorithm available in
> Mahout
>
> is logistic regression. You can force it to solve this problem in two
> ways. First, you can scale and offset the output by a large enough
> factor so that the normal 0 to 1 output range is much larger than
> necessary and the mean is centered at the rough mean of your data. The
> only input feature would be wakeup time.
>
> Another approach would be to use multinomial output with three outputs.
> This is a more natural fit to the Mahout algorithm.
>
> Is this a homework problem?
>
> On Wed, Jan 9, 2013 at 9:16 PM, akshay shetye
> <akshay.shetye@gmail.com>wrote:
>
>> I have a machine learning problem which i am illustrating by giving a
>> simile ,less complex example
>>
>> John goes from home to office daily.He takes following time to reach
>> to office
>>
>> Bus > 3 hours
>> Cab > 2 hours
>> bike > 1 hours
>>
>> Problem:How much time john will take to reach his office from the time
>> he starts.
>>
>> He mostly takes bus and sometimes cab and rarely bike depending on how
>> much time he has to reach his office
>>
>> He must reach at office at 9am.
>>
>> Now if he starts at 6 he takes bus
>> if he starts at 7 he takes cab
>> if he starts at 8 he takes bike.
>>
>> Now the model which i build using M5P and libSvm predicts fine when he
>> starts on or before 8.Now the problem occurs when John leaves his home
>> after 8 (eg 8.30 or 9 /assume he got up late) . Ideally in this case
>> he will take around 1 hour as he should take his bike.
>>
>> My model is giving me negative predictions and this is what is causing
>> problem.
>>
>> Now as john wakes up late very rarely we have very few data points to
>> train it on such cases.
>>
>> My feature list is as follows
>>
>> timeLeftForDuty, DAY_OF_WEEK , TRAVEL_TIME
>>
>> TRAVEL_TIME is we are trying to predict.
>>
>> How can solve this problem?Meaning how can i avoid getting negati
>> values of travel time?Which algorithm should i use from mahout?
>>
>> 
>> Regards,
>> Damodar Shetyo
>>
>
> Regards,
> Damodar Shetyo
>
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