This competition trains us in creating models using classification methods, where the predicted target is not a binary column such as 1 or 0. But rather predicting the probability of the target. This time I used the RandomforestClassifier, KNeighborsClassifier, and XGBClasifier methods. Where this model is evaluated using the ROC-AUC Score metric. in this model, the highest score is 0.70879 with a ranking of 1869. This is something new where I predict the model, but there is a challenge, namely the dataset imbalance with its target, because there is a problem, namely Oversampling. This is an attraction for me to train my skills in the world of Machine Learning. Hopefully this repository can help you in learning Beginner Machine Learning
- Pandas
- Numpy
- Sckit Learn
- JCOPML Package
- and another Library