Model Comparison Help

Benchmark multiple regressors (linear, trees, boosting, SVR, neural net) under the same cross-validation splits.

Requires: One dataset with a numeric target column.

Form fields accepted by this method's POST request

analysis_type=model_comparison, dataset_id, categorical_encoding, model_keys, n_splits, target_col, test_size

No dataset yet? Upload a file.
The numeric variable the models will predict.
Parameters & Options
The server uses the group matching the selected target's type (numeric → regression, text/categories → classification).
Regression models
Classification models
Leave all unchecked to use the default set (Linear/Logistic Regression, Random Forest, KNN).
How non-numeric feature columns are converted before modeling.
Optional: fill missing numeric values before the analysis runs. Leave as default to keep the method's own handling.
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