Model Info

Learn: 1.56420705e-05
Test: 0.6633280425
Learning time: 0 second
Feature names: Fixed acidity, Volatile acidity, Citric acid, Residual sugar, Chlorides, Free sulfur dioxide, Total sulfur dioxide, Density, pH, Sulphates, Alcohol
Feature importance:
Fixed acidity: 7.47%
Volatile acidity: 13.16%
Citric acid: 7.33%
Residual sugar: 6.66%
Chlorides: 7.67%
Free sulfur dioxide: 6.29%
Total sulfur dioxide: 11.81%
Density: 7.01%
pH: 5.91%
Sulphates: 12.05%
Alcohol: 14.65%
Model Size: 1.02 MB
Data Size: 0.1 MB
Algorithm: CatBoost (Gradient Boosting)
Tree Count: 500
Learning Rate: 1
One-Hot Max Size: 8
Test Size: 0.2
Shuffle Data: True
Use Best Model: False
nan_mode: Min
eval_metric: RMSE
iterations: 500
sampling_frequency: PerTree
leaf_estimation_method: Newton
grow_policy: SymmetricTree
penalties_coefficient: 1
boosting_type: Plain
model_shrink_mode: Constant
feature_border_type: GreedyLogSum
bayesian_matrix_reg: 0.1000000015
force_unit_auto_pair_weights: False
l2_leaf_reg: 3
random_strength: 1
rsm: 1
boost_from_average: True
model_size_reg: 0.5
pool_metainfo_options: {'tags': {}}
subsample: 0.8000000119
use_best_model: False
random_seed: 0
depth: 7
posterior_sampling: False
border_count: 254
classes_count: 0
auto_class_weights: None
sparse_features_conflict_fraction: 0
leaf_estimation_backtracking: AnyImprovement
best_model_min_trees: 1
model_shrink_rate: 0
min_data_in_leaf: 1
loss_function: RMSE
learning_rate: 1
score_function: Cosine
task_type: CPU
leaf_estimation_iterations: 1
bootstrap_type: MVS
max_leaves: 128