Scale and Standardize Heart Disease Dataset with sklearn

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Introduction

The UCI Heart Disease Dataset

Importing the libraries and the data

Descriptive Statistics

Data Distribution

Feature Scaling Methods

Implementing Standard Scaler using Python
The affect of using Minmax Scaler on the dataset
Implementing minmax Scaler using Python
The affect of using Robust Scaler on the dataset
Implementing Robust Scaler using Python
The affect of using Normalize Scaler on the dataset
Implementing Normalizer using Python

Machine Learning Algorithms Performance

ML Algorithms Before using the Robust ScalersLR: 0.690833 (0.067955)
LDA: 0.666333 (0.073295)
KNN: 0.681500 (0.063204)
CART: 0.731333 (0.059758)
NB: 0.670500 (0.085248)
SVM: 0.764167 (0.076939)
Before Applying the Robust Scaler
ML Algorithms After Using the Robust ScalersLR: 0.693833 (0.090419)
LDA: 0.702167 (0.074633)
KNN: 0.698833 (0.066186)
CART: 0.752000 (0.082774)
NB: 0.681500 (0.084217)
SVM: 0.743667 (0.100755)
After Applying the Robust Scaler

Conclusion

References

Writer, Engineer, Cyber security enthusiast ,PhD. Candidate & 4 Open Source write about my day to day experience in Software Data, and Engineering.

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