In this project, your aim is to leverage machine learning to automatically classify patients' examinations into five distinct classes using as predictors cardiac magnetic resonance radiomics.
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Baseline Model Development - tree-based classifier from scikit-learn #8
Baseline Model Development: Utilize AutoML/H20 initially, followed by a tree-based
classifier from scikit-learn, to develop a baseline model. Evaluate the model's
performance using various metrics while discussing potential model issues, as well as the
rationale behind the chosen evaluation metrics. Assess whether this model is acceptable,
providing reasons for your conclusion. Computational difficulties may be encountered
when performing AutoML due to the large number of predictive variables (features).
marcelokscunha
commented
3 months ago
Baseline Model Development: Utilize AutoML/H20 initially, followed by a tree-based classifier from scikit-learn, to develop a baseline model. Evaluate the model's performance using various metrics while discussing potential model issues, as well as the rationale behind the chosen evaluation metrics. Assess whether this model is acceptable, providing reasons for your conclusion. Computational difficulties may be encountered when performing AutoML due to the large number of predictive variables (features).