David Thrower

@sashakolpakov It looks like this approach Embedding -> dropout is a winner. I see that with the current params (that may no longer be optimal) I see test set binary-accuracy...

Fixed with: https://github.com/david-thrower/cerebros-mlflow-based/issues/15

@riteshnoronha , Thanks for the awesome and practical recommendation. I will prioritize this.

One possibility is: In .github/workflows/automerge.yaml, append: ```yaml # Add a pipeline step - name: Run Trivy vulnerability scanner in fs mode uses: aquasecurity/trivy-action@master with: scan-type: 'fs' scan-ref: '.' trivy-config: trivy.yaml...

1. Add a parameter for the problem at hand [classification | regression] 2. For binary classification, add a confusion matrix and a ROC curve. 3. For multi - class -...

Genomic research often will Z scale target phenotypes when they are doing regression based GWAS experiments. This makes it easy to quantify the RMSE / MAE in terms of standard...