##Peking University Machine Learning Homework two Group Member： zhouzhaoping dongzhuoyao snowingmush
Data Source:Image Segmentation data
####Basic Adaboost Binary-Classification
- decision_stump.py:
单层决策树的实现，buildStump接口找到当前加权数据集上的最优单层决策树 - adaboost.py:
基于单层决策树adaboost算法的类Adaboost，关键方法fit学习训练集和predict预测 - data_preprocess.py:
数据预处理
####OVR(one-versus-rest)
- one_versus_rest.py:
run Adaboost to implement one-versus-others multi-classification
precision recall f1-score support
BRICKFACE 0.55 0.99 0.71 300
CEMENT 0.83 0.65 0.73 300
FOLIAGE 0.88 0.81 0.84 300
GRASS 0.99 0.98 0.99 300
PATH 1.00 0.91 0.95 300
SKY 0.99 1.00 1.00 300
WINDOW 0.86 0.51 0.64 300
avg / total 0.87 0.84 0.84 2100
####OVO(one-versus-one)
- one_versus_rest.py:
run Adaboost to implement one-versus-one multi-classification
precision recall f1-score support
BRICKFACE 0.19 1.00 0.32 300
CEMENT 0.00 0.00 0.00 300
FOLIAGE 0.64 0.31 0.41 300
GRASS 1.00 0.95 0.97 300
PATH 0.00 0.00 0.00 300
SKY 0.03 0.00 0.01 300
WINDOW 0.87 0.11 0.20 300
avg / total 0.39 0.34 0.27 2100
####Adaboost.MH (Improved boosting algorithms using confidence-rated predictions)
- adaboostmh.py:
based on Adaboost，evolve into AdaBoostMH - run_adaboostmh.py:
precision recall f1-score support
BRICKFACE 0.60 0.99 0.74 300
CEMENT 0.80 0.63 0.71 300
FOLIAGE 0.86 0.81 0.83 300
GRASS 1.00 0.98 0.99 300
PATH 1.00 0.90 0.95 300
SKY 0.99 1.00 1.00 300
WINDOW 0.86 0.62 0.72 300
avg / total 0.87 0.85 0.85 2100
####How to run
cd PATH_TO_THE_PROJECT python one_versus_one.py python one_versus_rest.py python run_adaboostmh.py