/Comparative-Analysis-of-ML-Models

Classified the levels of anxiety among different age groups by various Machine Learning algorithms to predict the level of anxiety.

Primary LanguageJupyter Notebook

Comparative-Analysis-of-ML-Models

  • Classified the levels of anxiety among different age groups by various Machine Learning algorithms to predict the level of anxiety.
  • Conducted in-depth Exploratory Data Analysis (EDA) on a diverse dataset to gain insights into underlying patterns and trends.
  • Implemented and compared various machine learning models, including Logistic Regression, Decision Tree, and Support Vector Machine (SVM), to assess their prediction performance.
  • Employed Principal Component Analysis (PCA) to reduce dimensionality and enhance model efficiency.
  • Utilized GridSearchCV to fine-tune model hyperparameters and optimize model performance.
  • Employed K-Fold Cross Validation to evaluate model accuracy and Area Under the Curve (AUC) scores, providing a robust assessment of model performance.