I am really sorry if it is trivial.
Why is that running the trainlogistic with different rates and passes give
me same auc and confusion matrix result on the test data. Although the time
of training increases with number of passes but seems to have no effect on
result. I can understand that rate is the learning rate but what is the
purpose of passes?
I have split my data into 80% training and 20% Test data.
Training data size is 51000 (approx)
Test data size is 12000(approx)
Total size of the data is 63000 (approx)
I have gone through the explanations in MIA book chapter 13 but is there
any rule of thumb for deciding it?
Also, while training the model , the following output is not intuitive to
comprehend especially the last part of the output having quite a few zeros.
Any thoughts?
CLASS ~ -13.774*AON + 10.065*BALANCE + 28804.244*INDECRE +
-0.782*INDECRE_FREQ + -634.428*Intercept Term + 28804.244*MOU +
-1312.785*NO_VOICE_CALLS + -24613.959*OFFNET_USAGE + 118998.287*ONNET_USAGE
+ -634.428*RECHARGE + 118998.287*RECHARGE_FREQ + -1312.785*SMS
AON -13.77429
BALANCE 10.06540
INDECRE 28804.24420
INDECRE_FREQ -0.78217
Intercept Term -634.42839
MOU 28804.24420
NO_VOICE_CALLS -1312.78468
OFFNET_USAGE -24613.95945
ONNET_USAGE 118998.28731
RECHARGE -634.42839
RECHARGE_FREQ 118998.28731
SMS -1312.78468
-24613.959449080 28804.244197092 0.000000000 0.000000000
-1312.784681776 -634.428388766 10.065402474 0.000000000
-0.782170605 -13.774291103 118998.287306148
