[Urgent] Classifier on a small and clean dataset
$30-250 USD
Dibayar semasa penghantaran
The data is about loan performance (default or not) - it has 9000+ rows and very clean. You need to build a classifier (programmed in Python) with Random Forest and XGboost and do the usual evaluation based on CV. The features will be given to you, no feature engineering/selection on your end.
The only two slightly fancy requests - 1. when building the model, down sample the non-default group as the data is high unbalanced. 2. do some grid search of hyper-parameters for the Random Forest and XGboost models ( just two parameters for each model will do). This should take no more than 5 hours for an experienced data scientist.
It is very urgent and needs to be done in the next 10 hours. Thank you!
ID Projek: #19788457
Tentang projek
5 pekerja bebas membida secara purata $139 untuk pekerjaan ini
Dear sir. Your project attracted my attention at first glance, because I've extensive experience in Classification Programming. I'm really confident about your project, and very eager to join your project. If we ha Lagi
I am a Python developer with 4+ years of experience that specializes in multi-platform applications using PyQt, PySide/PyQt,Scrapy, BeautifulSoup 4, Pillow, Matplotlib, Xml, json, and csv modules, Celery I am also wor Lagi
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