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metadata
library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-classification
model_format: pickle
model_file: model.pkl
widget:
  - structuredData:
      blue_aggressiveness_score:
        - 1.292
        - 1
        - 1.115
      blue_avg_durability:
        - 4.8
        - 5.2
        - 5.2
      blue_avg_offense:
        - 6.2
        - 5.2
        - 5.8
      blue_early_mid_ratio:
        - 1
        - 0.667
        - 1.5
      blue_mid_late_ratio:
        - 1.5
        - 1.5
        - 2
      control_effects_diff:
        - -22
        - 0
        - -2
      difficulty_diff:
        - 7
        - 0
        - 5
      durability_diff:
        - -8
        - -11
        - 3
      offense_diff:
        - 5
        - 6
        - 0
      power_spike_diff:
        - -1
        - -1
        - -3
      red_aggressiveness_score:
        - 0.812
        - 0.541
        - 1.261
      red_avg_durability:
        - 6.4
        - 7.4
        - 4.6
      red_avg_offense:
        - 5.2
        - 4
        - 5.8
      red_early_mid_ratio:
        - 1
        - 1.333
        - 0.5
      red_mid_late_ratio:
        - 4
        - 3
        - 1.333

Model description

This is a RandomForestClassifier model trained on mpl_id_s14 dataset.

Intended uses & limitations

[More Information Needed]

Training Procedure

[More Information Needed]

Hyperparameters

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Hyperparameter Value
bootstrap True
ccp_alpha 0.0
class_weight
criterion gini
max_depth 2
max_features sqrt
max_leaf_nodes
max_samples
min_impurity_decrease 0.0
min_samples_leaf 8
min_samples_split 2
min_weight_fraction_leaf 0.0
monotonic_cst
n_estimators 50
n_jobs
oob_score False
random_state 91
verbose 0
warm_start False

Model Plot

RandomForestClassifier(max_depth=2, min_samples_leaf=8, n_estimators=50,random_state=91)
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Evaluation Results

[More Information Needed]

How to Get Started with the Model

[More Information Needed]

Model Card Authors

z4fL

Model Card Contact

You can contact the model card authors through following channels: [More Information Needed]

Citation

Below you can find information related to citation.

BibTeX:

[More Information Needed]

Limitations

This model is only trained with MPL ID Season 14 data

confusion_matrix

confusion_matrix