Description Usage Arguments Value Examples
Creates plot of training and test error for trained model.
1 2 | train_test_plot(model, score_type, x, y, hyperparameter, param_range,
random_seed)
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model: |
Currently only works with argument 'decision_tree'. Generally: String specifying decision_tree, lasso, ridge regression, or logistic regression. Argument should be one of "decision_tree", "lasso", "ridge", or "logistic".. |
score_type: |
(list or str): Should be one of (mse, r2, adj_r2, auc, ...). If a vector, then a vector containing several of those entries as elements |
x: |
n x d dataframe containing features |
y: |
n x 1 dataframe containing response values. |
hyperparameter: |
string defining hyperparameter to iterate over |
param_range: |
vector of hyperparameter values to iterate over |
random_seed: |
Default = None. If set to integer, defines the random train_test_split |
ggplot object showing training and test score vs. hyperparameter values.
1 2 3 4 5 6 7 | ## Not run: data('Sonar')
## Not run: X <- Sonar[,1:60]
## Not run: Y <- Sonar[,61]
## Not run: train_test_plot(model = "decision_tree", score_type = "accuracy", x = X,
y = Y, hyperparameter = "cp", param_range = c(0.1,0.2,0.3), random_seed=123)
## End(Not run)
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