This repository looks into various python-based machine learning and data science libraries in an attempt to build a machine learning model capable of predicting whether or not someone has heart disease based on their medical attributes.
- Problem Definition
- Data
- Evaluation
- Features
- Modeling
- Experimentation
In a statememt
Given clinical parameters about a patient, can we predict whether or not they have heart disease?
The original data came from the Cleveland database https://archive.ics.uci.edu/ml/datasets/heart+Disease from UCI Machine Learning Repository. Howevever, we've downloaded it in a formatted way from Kaggle https://www.kaggle.com/datasets/sumaiyatasmeem/heart-disease-classification-dataset .
If we can reach 95% accuracy at predicting whether or not a patient has heart disease during the proof of concept, we'll pursure this project.
This is where you'll get different information about each of the features in your data.
** Create Data Dictionary
- age: Displays the age of the individual.
- sex: Displays the gender of the individual using the following format : 1 = male 0 = female
- cp- Chest-pain type: displays the type of chest-pain experienced by the individual using the following format :
- 0 = typical angina
- 1 = atypical angina
- 2 = non โ anginal pain
- 3 = asymptotic
- trestbps- Resting Blood Pressure: displays the resting blood pressure value of an individual in mmHg (unit). anything above 130-140 is typically cause for concern.
- chol- Serum Cholestrol: displays the serum cholesterol in mg/dl (unit)
- fbs- Fasting Blood Sugar: compares the fasting blood sugar value of an individual with 120mg/dl. If fasting blood sugar > 120mg/dl then : 1 (true) else : 0 (false) '>126' mg/dL signals diabetes
- restecg- Resting ECG : displays resting electrocardiographic results 0 = normal 1 = having ST-T wave abnormality 2 = left ventricular hyperthrophy
- thalach- Max heart rate achieved : displays the max heart rate achieved by an individual.
- exang- Exercise induced angina : 1 = yes 0 = no
- oldpeak- ST depression induced by exercise relative to rest: displays the value which is an integer or float.
- slope- Slope of the peak exercise ST segment : 0 = upsloping: better heart rate with excercise (uncommon) 1 = flat: minimal change (typical healthy heart) 2 = downsloping: signs of unhealthy heart
- ca- Number of major vessels (0โ3) colored by flourosopy : displays the value as integer or float.
- thal : Displays the thalassemia : 1,3 = normal 6 = fixed defect 7 = reversible defect: no proper blood movement when excercising
- target : Displays whether the individual is suffering from heart disease or not : 1 = yes 0 = no