搜索资源列表
ML
- ML 频偏算法 一个比较经典的算法 很有用-ML offset a more classical algorithm algorithm useful
ML
- 《空间谱估计理论与算法》一书中介绍的ML最大似然算法，如果有用请点推荐-ML maximum likelihood algorithm " spatial spectrum estimation theory and algorithms," a book described, if helpful please recommend
ML-Rician
- ML for Rice channel. all supporting file included.
Ml函数
- Ml函数的而参数代码，对于分数阶微积分中用到的有极大的帮助
ML
- 最大似然法（Maximum Likelihood，ML）也称为最大概似估计，也叫极大似然估计，是一种具有理论性的点估计法，此方法的基本思想是：当从模型总体随机抽取n组样本观测值后，最合理的参数估计量应该使得从模型中抽取该n组样本观测值的概率最大，而不是像最小二乘估计法旨在得到使得模型能最好地拟合样本数据的参数估计量。-Maximum likelihood method (Maximum Likelihood, ML), also known as maximum likelihood estim
ML
- 正交频分复用系统ofdm中传统的ml频偏估计算法-Orthogonal frequency division multiplexing system ofdm in the traditional ml frequency offset estimation algorithm
ML-Navie-Baye
- 相关机器学习，ML-Naive，R语言学习。-Related to machine learning, ML-Naive, R language learning.
ML-kNN
- 本程序实现了融合最近邻的ML-KNN算法（即IML-KNN），与KNN进行比较，分类效果更好。-This procedure to achieve the fusion of the nearest neighbor ML-KNN algorithm (ie IML-KNN), compared with KNN, better classification effect.
粒子群优化算法
- MATLAB算法，粒子束优化算法(IPSO)，同时包含各种算法比较算法，ML、OSIC、IPSO(MATLAB algorithm, particle beam optimization algorithm (IPSO), including a variety of algorithm comparison algorithm, ML, OSIC, IPSO)
ML-CFAR
- 用於雷達檢測的ml-cfar matlab代碼(ml- cfar matlab code for radar detection)
ml-startup-1
- 线型模型的学习资料 python源码，依赖sk-lean库实现(Linear model of learning materials Python source code, relying on sk-lean library implementation)
Machine learning
- Supervised learning ML
Machine learning
- ML supervised learning
ML-MATLAB-code-master
- Andrew Ng's ML-MATLAB-code-mastermy matlab code for the homework of machine learning course
reset 1660
- Samsung ML-1660 frimeware reset
1660_30
- Samsung Printer V30 ml 1660
a01
- 利用ML算法对训练集进行学习，利用多维高斯进行判断后对输入图片进行前景后景判断(The training set for learning to use ML algorithm to judge on the input image foreground & background)
ml.tar
- machine learning
ml1.tar
- ml instruction
Spark
- 主要有介个ml模型，可以有ALS推荐，SVM 分类(There are mainly ml models, which can be classified by ALS and SVM.)