Anxiety-level-classification

Anxiety disorders affect millions globally, and accurate classification of anxiety levels can help in better diagnosis and treatment planning. This project utilizes a dataset with demographic, psychological, and behavioral variables to classify anxiety levels into 4 distinct categories as Mild, None-minimal,Moderate and Severe.

Dataset Description

The dataset consists of 1566 records with the following key features:

1. age (int): Age of the individual.
2. gender (object): Gender of the individual
3. bmi (float): Body Mass Index of the individual
4. who_bmi (object): BMI category based on WHO standards.
5. phq_score (int): Patient Health Questionnaire score.
6. depression_severity (object): Severity of depression.
7. depressiveness (object): Self-reported level of depressiveness.
8. suicidal (object): Suicidal tendencies
9. depression_diagnosis (object): History of depression diagnosis.
10. depression_treatment (object): History of receiving depression treatment.
11. anxiety_diagnosis (object): History of anxiety diagnosis.
12. anxiety_treatment (object): History of receiving anxiety treatment.
13. epworth_score (float): Epworth Sleepiness Scale score.
14. sleepiness (object): Self-reported level of sleepiness.
15. anxiousness (object): Self-reported level of anxiousness.
16. anxiety_severity (object): Severity of anxiety.

Source:

https://www.kaggle.com/datasets/mahmoudosama22/anxiety-dataset

Used Models

1. Decsion tree
2. Random Forest
3. Gradient Bossting
4. XGBoost
5. Ensemble methods(Voting & Stacking classifier)