Alvin Smart Money Management Classification Challenge
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Helping Kenya
$3 000 USD
Challenge completed ~3 years ago
Classification
497 joined
220 active
Start
Jun 22, 22
Close
Jul 24, 22
Reveal
Jul 24, 22
What Cross-validation Techniques are you using?
Help · 27 Jun 2022, 11:33 · 11
I observe that education and rental mortgage have two values each in the training dataset. I can not fit my data with stratified or K-fold cross-validation. What is your opinion and solution to this?
Might not be entirely right tho, try and use the train set to predict the missing target on the extra data b4 u do the main work. This might help.
Thanks, I will look into that.
if we use the train set to predict the missing target on the extra data, and use it to train a model, there is a big chance to train the model with wrong labels
I used StratifiedShuffleSplit and it worked, using StratifiedKFoldSplit will work if you don't set shuffle=True, since it creates a random fold each time, and education and rental mortgage might just be in one, and also trying encoding the target class that will help
Yes, that is my observation. i am using train_test_split.
you can use StratifiedKFoldSplit it will work with you it is better for our case.
There is 2 categories in the target variable that occurs twice?.
please clarify more ?
If you checked the target variable distribution, Health and Rent mortgage has 2 values in the training data.
I believe this is bcos the data is an imbalance dataset that can be solve with smote, down sampling or over
I used stratifiedshufflesplit and it worked, try using train_test_split