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: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.

Training Procedure

[More Information Needed]

Hyperparameters

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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

[More Information Needed]

Model Card Authors

gianlab

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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