newsReddit r/MachineLearningTrust 52 · CommunityPublished 1mo agoLive · 1mo ago
Hyperparameter tuning approach question [R]
I am doing some work with cell type classification, where I have 4.3 million cells and 512 features (condensed embeddings from the encoder of a transformer). The broader goal is to implement a contextual bandit for augmenting the training set of the dataset, as it is currently imbalanced, and rare cell type classification is poor when I tried a baseline logistic regression classifier. Dataset: Feature matrix shape: (4290471, 512) Labels
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- PossiblePossibly related (embedding) · 49%Fine-tuning →
- PossiblePossibly related (embedding) · 45%optuna/optuna →
- PossiblePossibly related (embedding) · 45%rodrigo-arenas/Sklearn-genetic-opt →
- PossiblePossibly related (embedding) · 46%Diversified Multinomial Logit Contextual Bandits →
