Implementation of Gaussian Naive Bayes classification algorithm in Python using Pandas, NumPy and Scikit-Learn.
Classifier is being tested on sklearn "toy" datasets:
- Iris plant dataset
- Wine recognition dataset
- Breast cancer wisconsin (diagnostic) dataset
For each of the datasets I've used a different cross-validation method.
The goal of classification task - predicting target attribute of each dataset based on the rest of the attributes.