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Model description

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Intended uses & limitations

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Training Procedure

Hyperparameters

The model is trained with below hyperparameters.

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Hyperparameter Value
bootstrap True
ccp_alpha 0.0
class_weight
criterion gini
max_depth
max_features sqrt
max_leaf_nodes
max_samples
min_impurity_decrease 0.0
min_samples_leaf 1
min_samples_split 2
min_weight_fraction_leaf 0.0
n_estimators 25
n_jobs -1
oob_score False
random_state 1
verbose 0
warm_start False

Model Plot

The model plot is below.

RandomForestClassifier(n_estimators=25, n_jobs=-1, random_state=1)
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Evaluation Results

You can find the details about evaluation process and the evaluation results.

Metric Value
accuracy 0.988057
f1 score 0.988057

How to Get Started with the Model

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Model Card Authors

This model card is written by following authors:

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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:

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citation_bibtex

bibtex @inproceedings{...,year={2023}}

get_started_code

import pickle with open(dtc_pkl_filename, 'rb') as file: clf = pickle.load(file)

model_card_authors

Marvin Lomo

limitations

This model is not ready to be used in production.

model_description

This is a RandomForrestClassifier model trained on SME Churn Dataset.

eval_method

The model is evaluated using test split, on accuracy and F1 score with macro average.

confusion_matrix

confusion_matrix

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