Implementation of Categorical Naive Bayes classification algorithm in Python using Pandas, NumPy and Scikit-Learn.

Classifier is being fit with "categ.csv" dataset. Then it's tested on both "categ.csv" and "categ2.csv" datasets.

Both datasets have information about clothing.

Datasets characteristics:

• Number of instances: 1000
• Number of attributes: 5 (including target attribute), all categorical
• Attribute information:
  • size (XS, S, M, L, XL, XXL, 3XL)
  • material (nylon, polyester, silk, cotton, linen)
  • color (white, cream, blue, black, orange, green, yellow, red, violet, navy)
  • sleeves (short, long)
  • demand (low, medium, high)

The goal of classification task - predicting clothing demand based on the rest of the attributes.