experiment-design
Experiment Design
Design rigorous machine learning experiments that produce credible, reproducible results.
Design Checklist
Work through each section before writing any code.
1. Hypothesis
State the hypothesis as a falsifiable claim:
"We claim that [method X] achieves [metric Y] on [dataset Z] because [mechanism]."
If the hypothesis is vague, help the user sharpen it before proceeding.
2. Independent and Dependent Variables
- Independent variable: What is being changed (e.g., architecture, loss function, data augmentation)?
- Dependent variable: What is being measured (e.g., accuracy, FID score, wall-clock time)?
- Controlled variables: List everything held constant.
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