It is an assignment for [DS4013 Data Mining] in BNU-HKBU United International College Data-Science undergraduate programm.
This repository contains implementations of k Nearest Neighbor Algorithm, Naive Bayes Classification and Perceptron Classification in plain Python (Python Version 3.6+). These three algorithms are implemented from scratch without using additional machine learning libraries. Besides, this repository contains 5 classifiers by scikit-learn.
- k Nearest Neighbor Algorithm
- Naive Bayes Classification
- Perceptron Classification
Implemented through scikit-learn：
- Decision Tree Classifiers
- Random Forest Classifier
- AdaBoost Classifier
- Bagging Classifier
- Linear Discriminant Analysis
This dataset has 9 attributes with 3 classes
- A {1,-1,0}
- B {-1,0,1}
- C {1,-1,0}
- D {-1,0,1}
- E {-1,0,1}
- F {1,0,-1}
- G {1,-1,0}
- H {1,-1}
- I {0,1}
- Class {0,1,-1}