the mathematical knowledge

目录

• 1.The Mathematical Knowledge Needed For Machine Learning
• The Unknown Word

1.The Mathematical Knowledge Needed For Machine Learning

The First Column	The Second Column
algorithems	Mathematics
Bias classifier	random variable,Bias formula,Independence of random variables,Normal distribution,Maximum likelihood estimation
decision tree	probability,entropy,Gini coefficient
KNN algorithems	distance function
Main component analysis	Covariance Matrix,Scatter Matrix,
manifold learning	manifold,optimisation，Geodesic line,Geodesic distance,chart,Eigenvalue and Characteristic matrix
SVM	The distance from the point to the plane,Slater condition,Strong Dual,
logistic	probality,Discrete random variable,lagrange duality,KKT condition,Convex optimization,kernel function,Mercer Condition
logistic	probability,random variable,Maximum likelihood estimation,Gradient descent method,Convex optimization,Newton method
Random Forest	sampling,variance
AdaBoolslt algorithm	probability,Random variance,extreme value theory,Mathematical expectation,Newton method
Hidden Markov model	probability,Discrete random variable,

The Unknown Word

The First Column	The Second Column
scatter	['skaete]散开
formular	['fo:rmjule]公式
likelihood estimation	似然估计
entropy	['entrepi]熵
covariance	协方差
manifold	流行
optimisation	优化[optimai'seition]
geodesics	[dgi:ou'desics]测地线
geodesic	[dgi:ou'desik]测量的
eigenvalue	['aidjen vaelju:]特征值
discrete	离散的，分布的
logistic	逻辑的[lo'dgistik]
extreme value theory	极值定理
convex	凸的['konveks]
Random Forest	sampling,variance
discrete	分散的[di'skrit]

转载于:https://www.cnblogs.com/hugeng007/p/9380173.html

来源：CSDN

作者：weixin_30933531

链接：https://blog.csdn.net/weixin_30933531/article/details/95058609