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metadata
license: apache-2.0
library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-classification
model_format: pickle
model_file: skops-iw9h_jza.pkl
widget:
  - structuredData:
      x0:
        - 3
        - 5
        - 1
      x1:
        - 5
        - 5
        - 3
      x10:
        - 0
        - 0
        - 0
      x11:
        - 0
        - 0
        - 0
      x12:
        - 0
        - 0
        - 0
      x13:
        - 0
        - 0
        - 0
      x14:
        - 0
        - 0
        - 0
      x15:
        - 0
        - 0
        - 0
      x16:
        - 0
        - 0
        - 0
      x2:
        - 3
        - 4
        - 0
      x3:
        - 5
        - 4
        - 0
      x4:
        - 4
        - 4
        - 0
      x5:
        - 4
        - 0
        - 0
      x6:
        - 3
        - 0
        - 0
      x7:
        - 2
        - 0
        - 0
      x8:
        - 3
        - 0
        - 0
      x9:
        - 0
        - 0
        - 0

Model description

This model was created following the instructions in the following Kaggle notebook:https://www.kaggle.com/code/thedankdel/disease-symptom-prediction-ml-99The possible classified diseases are:The possible symptoms are:

Intended uses & limitations

This model follows the limitations of the Apache 2.0 license.

Training Procedure

[More Information Needed]

Hyperparameters

Click to expand
Hyperparameter Value
bootstrap True
ccp_alpha 0.0
class_weight
criterion gini
max_depth 13
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 500
n_jobs
oob_score False
random_state 42
verbose 0
warm_start False

Model Plot

RandomForestClassifier(max_depth=13, n_estimators=500, random_state=42)
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.

Evaluation Results

Metric Value
accuracy 0.995935
f1 score 0.995935

Model description/Evaluation Results/Classification report

index precision recall f1-score support
(vertigo) Paroymsal Positional Vertigo 1 1 1 18
AIDS 1 1 1 20
Acne 1 1 1 32
Alcoholic hepatitis 1 1 1 29
Allergy 1 0.947368 0.972973 19
Arthritis 1 1 1 31
Bronchial Asthma 1 1 1 28
Cervical spondylosis 0.9375 1 0.967742 30
Chicken pox 1 1 1 27
Chronic cholestasis 1 1 1 19
Common Cold 1 1 1 25
Dengue 1 1 1 22
Diabetes 1 1 1 23
Dimorphic hemmorhoids(piles) 1 1 1 30
Drug Reaction 1 1 1 21
Fungal infection 1 1 1 25
GERD 1 1 1 24
Gastroenteritis 1 0.95 0.974359 20
Heart attack 1 1 1 18
Hepatitis B 1 1 1 28
Hepatitis C 1 1 1 19
Hepatitis D 1 1 1 22
Hepatitis E 1 1 1 30
Hypertension 1 0.931034 0.964286 29
Hyperthyroidism 1 1 1 24
Hypoglycemia 1 1 1 27
Hypothyroidism 1 1 1 28
Impetigo 1 1 1 24
Jaundice 1 1 1 25
Malaria 1 1 1 26
Migraine 1 1 1 18
Osteoarthristis 1 1 1 20
Paralysis (brain hemorrhage) 0.904762 1 0.95 19
Peptic ulcer diseae 1 1 1 27
Pneumonia 1 1 1 21
Psoriasis 1 1 1 22
Tuberculosis 1 1 1 23
Typhoid 1 1 1 20
Urinary tract infection 1 1 1 24
Varicose veins 1 1 1 26
hepatitis A 1 1 1 21
macro avg 0.996153 0.995815 0.995838 984
weighted avg 0.996256 0.995935 0.995955 984

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

BibTeX

@inproceedings{...,year={2020}}