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About the Dataset:

age - age of patient

sex - 0: female, 1:males

cp - Chest Pain type Value 1: typical angina Value 2: atypical angina Value 3: non-anginal pain Value 4: asymptomatic

trtbps - Resting Blood Pressure (in mm Hg)

chol - Cholestroal (in mg/di) fetched via BMI sensor

fbs - (fasting blood sugar > 120 mg/dl) (1 = true; 0 = false)

restecg - resting electrocardiographic results Value 0: normal Value 1: having ST-T wave abnormality (T wave inversions and/or ST elevation or depression of > 0.05 mV) Value 2: showing probable or definite left ventricular hypertrophy by Estes' criteria

thalachh - maximum heart rate achieved

exng - exercise induced angina (1 = yes; 0 = no)

oldpeak - Previous peak

slp - Slope

caa - number of major vessels (0-3)

thall - Thal rate

output - Chance of heart attack (1 for more chance / 0 for less chance)

About

Exploratory ML using Logistic Regression, GaussianNB, KNN, Decision Trees, Random Forest & SVC. Highest accuracy (86.9%) with Random Forest, but needs work for real-world use.

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