---
license: apache-2.0
library_name: sklearn
tags:
- sklearn
- skops
- tabular-classification
model_format: pickle
model_file: skops-xwel2v4p.pkl
widget:
- structuredData:
    age:
    - 40
    - 21
    - 55
    alamine_aminotransferase:
    - 232
    - 36
    - 112
    albumin_and_globulin_ratio:
    - 0.8
    - 1.34
    - 0.8
    alkaline_phosphotase:
    - 293
    - 150
    - 482
    gender:
    - 0
    - 1
    - 1
    total_bilirubin:
    - 0.9
    - 3.9
    - 0.8
---

# 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

<details>
<summary> Click to expand </summary>

| 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   |

</details>

### Model Plot

<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-1" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>ExtraTreesClassifier(random_state=123)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-1" type="checkbox" checked><label for="sk-estimator-id-1" class="sk-toggleable__label sk-toggleable__label-arrow">ExtraTreesClassifier</label><div class="sk-toggleable__content"><pre>ExtraTreesClassifier(random_state=123)</pre></div></div></div></div></div>

## 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