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numpy 实现的周志华《机器学习》书中的算法及其他一些传统机器学习算法

Python 100.00%

python3 numpy svm lr ensemble boosting machine-learning clustering decision-tree gbdt

tiny_ml's Introduction

tinyml

利用numpy实现的一些周志华《机器学习》（西瓜书）一书及斯坦福cs229课程中的算法，宜配合西瓜书和cs229课件食用。并选择性实现了一些经典算法的简易版本，如按照陈天奇的slides实现的XGBRegressor。

已经实现的算法

和sklearn实现的比较

回归算法结果 代码

Algorithm vs. RMSE	sklearn-boston
Algorithm vs. RMSE	tinyml	sklearn
LinearRegression	27.196	27.196
SGDRegressor	27.246	27.231
DecisionTreeRegressor	21.887	21.761
RandomForestRegressor	21.142	21.142
GradientBoostRegressor	16.778	16.106
XGBRegressor	20.149	15.7

分类算法结果 代码

Algorithm vs. RMSE	sklearn-breast_cancer
Algorithm vs. RMSE	tinyml	sklearn
NaiveBayes	90.64%	90.64%
LogisticRegression	92.98%	92.98%
LDA	94.15%	92.40%
GDA	92.40%	93.57%
SVC	86.55%	92.98%
AdaboostClassifier	92.40%	92.40%

聚类算法比较 代码
KMeans

tinyml KMeans

sklearn KMeans

DBSCAN

tinyml DBSCAN

sklearn DBSCAN

GMM

tinyml GMM

sklearn GMM

AGNES

tinyml AGNES

sklearn AGNES

降维算法比较 代码
PCA

tinyml PCA

sklearn PCA

KernalPCA

tinyml KernalPCA

sklearn KernalPCA

LLE

tinyml LLE

sklearn LLE

MDS

tinyml MDS

sklearn MDS

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