Practical Tips For Binary Classification Excellence
Patrycja | Marketing Assistant at https://neptune.ai
Imagine if you could get all the tips and tricks you need to tackle a binary classification problem on Kaggle or anywhere else. I have gone over 10 Kaggle competitions including:
- Toxic Comment Classification Challenge $35,000
- TalkingData AdTracking Fraud Detection Challenge $25,000
- IEEE-CIS Fraud Detection $20,000
- Jigsaw Multilingual Toxic Comment Classification $50,000
- RSNA Intracranial Hemorrhage Detection $25,000
- SIIM-ACR Pneumothorax Segmentation $30,000
- Jigsaw Unintended Bias in Toxicity Classification $65,000
- Santander Customer Transaction Prediction $65,000
- Microsoft Malware Prediction $25,000
- Humpback Whale Identification $25,000
– and pulled out that information for you.
Dealing with imbalance problems
Cross-validation + proper evaluation
Averaging over multiple seeds
Average different models
Repositories and open solutions
Repos with open source solutions
Image based solutions
Tabular based solutions
Text classification based solutions
Hopefully, this article gave you some background into binary classification tips and tricks, as well as, some tools and frameworks that you can use to start competing.
We’ve covered tips on:
- tools and frameworks.
If you want to go deeper, simply follow the links and see how the best binary classification models are built.
This article was originally written by Derrick Mwiti and posted on the Neptune blog. You can find more in-depth articles for machine learning practitioners there.
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