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)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 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:
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Citation
Below you can find information related to citation.
BibTeX:
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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 
