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the mathematical knowledge

时间:2018-07-28 00:08:46      阅读:153      评论:0      收藏:0      [点我收藏+]

标签:ada   cal   ali   ble   ret   gradient   model   efficient   rest   

目录

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]

the mathematical knowledge

标签:ada   cal   ali   ble   ret   gradient   model   efficient   rest   

原文地址:https://www.cnblogs.com/hugeng007/p/9380173.html

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