Update package/samplers/smac_sampler/README.md

Co-authored-by: Naoto Mizuno <[email protected]>

package/samplers/smac_sampler/README.md

@@ -27,7 +27,7 @@ Please check the API reference for more details:
 - `surrogate_model_rf_ratio_features`: The ratio of features to use for each tree training in random forest. Equivalent to `max_features` in `RandomForestRegressor` in sklearn.
 - `surrogate_model_rf_min_samples_split`: The minimum number of samples required to split an internal node: Equivalent to `min_samples_split` in `RandomForestRegressor` in sklearn.
 - `surrogate_model_rf_min_samples_leaf`: The minimum number of samples required to be at a leaf node. A split point at any depth will only be considered if it leaves at least `min_samples_leaf` training samples in each of the left and right branches. This may have the effect of smoothing the model, especially in regression. Equivalent to `min_samples_leaf` in `RandomForestRegressor` in sklearn.
-  `init_design_n_configs`: Number of initial configurations.
+- `init_design_n_configs`: Number of initial configurations.
   `init_design_n_configs_per_hyperparameter`: Number of initial configurations per hyperparameter. For example, if my configuration space covers five hyperparameters and `n_configs_per_hyperparameter` is set to 10, then 50 initial configurations will be sampled.
   `init_design_max_ratio`: Use at most `n_trials * init_design_max_ratio` number of configurations in the initial design. Additional configurations are not affected by this parameter.
   `output_directy` : `Path`, defaults to `Path("smac3_output")`. The directory in which to save the output. The files are saved in `./output_directory/name/seed`.