metadata
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
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)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
ExtraTreesClassifier(random_state=123)
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