Model description

This model was created following the instructions in the following Kaggle notebook:

https://www.kaggle.com/code/michalbrezk/xgboost-classifier-and-hyperparameter-tuning-85

The possible classified predictions are: 'Non liver patient', 'Liver patient'

The predictors are: age, gender, total_bilirubin, alkaline_phosphotase, alamine_aminotransferase, albumin_and_globulin_ratio

Intended uses & limitations

This model follows the limitations of the Apache 2.0 license.

Hyperparameters

Click to expand

Hyperparameter	Value
bootstrap	False
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	100
n_jobs
oob_score	False
random_state	123
verbose	0
warm_start	False

Model Plot

ExtraTreesClassifier(random_state=123)

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Evaluation Results

Metric	Value
accuracy	0.836538
f1 score	0.836538

Model description/Evaluation Results/Classification report

index	precision	recall	f1-score	support
Liver patient	0.814159	0.87619	0.844037	105
Non liver patient	0.863158	0.796117	0.828283	103
macro avg	0.838659	0.836153	0.83616	208
weighted avg	0.838423	0.836538	0.836236	208

How to Get Started with the Model

To use the AI model run the following code on Google Colab:

https://colab.research.google.com/drive/1OKyEMTrrBqjdc9_3wgnn_ZHaRYMmr7mx?usp=sharing