README.md

metadata

license: apache-2.0
library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-classification
model_format: pickle
model_file: skops-rsihc7ad.pkl
widget:
  - structuredData:
      Age:
        - 52
        - 52
        - 37
      Annual income from social welfare programs:
        - 0
        - 0
        - 0
      Education:
        - 5
        - 2
        - 3
      Gender:
        - 0
        - 1
        - 1
      I am currently employed at least part-time:
        - 1
        - 1
        - 1
      I have a gap in my resume:
        - 0
        - 0
        - 0
      I have my regular access to the internet:
        - 1
        - 1
        - 1
      I live with my parents:
        - 0
        - 0
        - 0
      I read outside of work and school:
        - 1
        - 1
        - 1
      Income:
        - 7
        - 28
        - 100
      Lack of concentration:
        - 0
        - 0
        - 0
      Tiredness:
        - 0
        - 1
        - 1
      Unemployed:
        - 0
        - 0
        - 0

Model description

The possible classified predictions are:

'No Mental Illness', 'Yes Mental Illness'

The predictors are:

'I am currently employed at least part-time', 'Education' , 'I have my regular access to the internet', 'I live with my parents', 'I have a gap in my resume', 'Income', 'Unemployed', 'I read outside of work and school','Annual income from social welfare programs', 'Lack of concentration', 'Tiredness', 'Age', 'Gender'

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
covariance_estimator
n_components
priors
shrinkage
solver	svd
store_covariance	False
tol	0.0001

Model Plot

LinearDiscriminantAnalysis()

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Evaluation Results

Metric	Value
accuracy	0.835821
f1 score	0.835821

Model description/Evaluation Results/Classification report

index	precision	recall	f1-score	support
No Mental Illness	0.847458	0.961538	0.900901	52
Yes Mental Illness	0.75	0.4	0.521739	15
macro avg	0.798729	0.680769	0.71132	67
weighted avg	0.825639	0.835821	0.816014	67

How to Get Started with the Model

To use the model run the code in this Google Colab notebook:

https://colab.research.google.com/drive/1jBrTTNYGn0dWx3it9CVovc1uFZxNsYHO?usp=sharing