Timeline for Why doesn't Mahout logistic regression give a good AUC when the model is tested on training data?
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
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| Jan 20, 2015 at 13:05 | vote | accept | Emre Sevinç | ||
| Jan 19, 2015 at 10:16 | history | edited | Scortchi♦ | CC BY-SA 3.0 |
fixed typos, formatted code
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| Jan 19, 2015 at 10:13 | comment | added | Emre Sevinç | According to the resources above, "--rate Sets the initial learning rate. This can be large if you have lots of data or use lots of passes because it’s decreased progressively as data is examined." and in the example it is set to 50 (because in the example there are lots of passes). In my case I set it to 100 because I assumed my data was large enough (see above). Again, my assumption might have been totally wrong. | |
| Jan 19, 2015 at 10:09 | comment | added | Emre Sevinç | According to slideshare.net/tanuvir/logistic-regression-using-mahout and the book "Mahout in Action", "--passes Specifies the number of times the input data should be reexamined during training. Small input files may need to be examined dozens of times. Very large input files probably don’t even need to be completely examined." I assumed 7 million lines with 18 attributes was a very large file, this is why I did "--passes 2". But of course I might be totally wrong. I'll try with more passes. | |
| Jan 19, 2015 at 9:41 | history | answered | rapaio | CC BY-SA 3.0 |