Exploratory Data Analysis and Modeling of Parkinsons Disease Diagnosis Using Classification Algorithms

The project included an exploratory data analysis and evaluation of binary classification algorithms using Python sci-kit learn Logistic Regression, Random Forest Classification, Gradient Boosting Classification, Support Vector Machine Classifier, and KNN Classifier. Model were trained and tested and test accuracy was compared to arrive at a final model.

Objective:

The objective of the project was to build a predictive model for Parkinsons Disease diagnosis.

Dataset source: https://www.kaggle.com/datasets/rabieelkharoua/parkinsons-disease-dataset-analysis/data

Data Contents:

This dataset comprises comprehensive health information for 2,105 patients diagnosed with Parkinson's Disease, each uniquely identified with IDs ranging from 3058 to 5162. The dataset includes demographic details, lifestyle factors, medical history, clinical measurements, cognitive and functional assessments, symptoms, and a diagnosis indicator. This dataset is valuable for researchers and data scientists aiming to explore factors associated with Parkinson's Disease, develop predictive models, and conduct statistical analyses.

The dataset includes additional data in the following categories.

• Patient Information
• Patient ID
• Demographic Details
• Lifestyle Factors
• Medical History
• Clinical Measurements
• Cognitive and Functional Assessments
• Symptoms
• Diagnosis Information
• Confidential Information Information

Authors

• @wlouer

Acknowledgements

• The dataset was aquired from Kaggle user https://www.kaggle.com/rabieelkharoua

🚀 About Me

I'm Bill—a power industry professional with 20+ years of experience in power generation. My background as a mechanical engineer led to me a role as project manager where I led the development and execution of power generation projects. These days, I'm diving into data science, visualization, and machine learning with the intention of using it as a tool to uncover insights and improve decision making in power project development, design, procurement, construction and operations.