New Kernel‑Density Method Improves Imbalanced Binary Classification

KOTARO (Kernel‑density‑Oriented Threshold Adjustment) improves minority‑class recall on synthetic and public imbalanced datasets and can be added post‑hoc to any binary model. getnews.me/new-kernel-density-metho... #machinelearning #imbalanceddata

ADASYN: Adaptive Synthetic Sampling for Imbalanced Datasets - Train in Data's Blog ADASYN can be used to handle data imbalance by creating synthetic samples of the minority class and improve model performance. Really?

Imbalanced datasets can mess with your ML models. 😬
ADASYN (Adaptive Synthetic Sampling) to the rescue! 🚀

Learn how it works + when to use it in our latest blog 👇
https://f.mtr.cool/rqstrumpnx

#MachineLearning #DataScience #ImbalancedData #ADASYN

Next Monday on Data Bites : Probe Feature Selection

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https://f.mtr.cool/xefqrzzgeh

#machinelearning #datascience #imbalanceddata #undersampling #mlmodels #ML

How do you handle imbalance in your ML workflows?

Drop your thoughts in the comments! Let's start a conversation about responsible and effective machine learning practices. 💬👇

onlinelibrary.wiley....

#MachineLearning #DataScience #AI #SMOTE #ImbalancedData #MLResearch #PredictiveModeling

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So much for fairness of financial decisions when granting credit?

The dirty secrets of SMOTE -> lnkd.in/epH_gi9K

#imbalanceddata hashtag#calibration
#conformalprediction

Although imbalance correction improved the balance between sensitivity and specificity, similar results were obtained by shifting the probability threshold instead.”

#imbalanceddata #conformalprediction #calibration

Stop oversampling! Changing the cutoff in probabilistic classifiers is enough for imbalanced data.
In our new paper, Gabriel O. Assunção, Marcos O. Prates, and I explore this in depth. jds-online.org/journal/JDS/...
#DataScience #MachineLearning #ImbalancedData #AI #Oversampling