Gradient Boosted Trees for Classification in Python

Step-by-step follow-along | Data Series | Episode 11.8

An explanation of Gradient Boosted Trees for Classification: Episode 11.7

You can view and use the code and data in this episode here: Link

Objective

Produce gradient boosted trees to diagnose individuals with heart disease.

Diagnosis of heart disease is defined as > 50% diameter narrowing of a major blood vessel.

Age - The person’s age in years
Sex - The person’s Gender (1= Male, 0 = Female)
ChestPainType - TA - typical angina, ATA - atypical angina
NAP - non-anginal pain, ASY - asymptomatic
RestingBP - Resting blood pressure (in mm Hg on admission to the
hospital)
Cholesterol - serum cholestoral in mg/dl
FastingBS - (fasting blood sugar > 120 mg/dl) (1 = true, 0 = false)
RestingECG - resting electrocardiographic results: normal, ST - having ST-T wave abnormality (T wave inversions and/or ST elevation or depression of > 0.05 mV), LVH - showing probable or definite left ventricular hypertrophy
by Estes’ criteria
MaxHR - maximum heart rate achieved
ExerciseAngina …