搜索资源列表
SVM
- 在机器学习领域，支持向量机SVM(Support Vector Machine）是一个有监督的学习模型，通常用来进行模式识别、分类、以及回归分析。-In the field of machine learning, support vector machine SVM (Support Vector Machine) is a supervised learning model, typically used for pattern recognition, classification, an
FullBNT-1.0.4
- Bayesian 神经网络，可用于模型构建中变量的筛选-Bayesian neural network，could be applied for variable selection in model construction
ctssvm--bfgs
- 对无约束的优化模型利用BFGS算法进行求解-For unconstrained optimization model uses BFGS algorithm to solve
tssvm--bfgs
- 对三次样条函数的模型利用BFGS算法进行优化求解-Cubic spline function model using BFGS algorithm optimization solution
Linear-classifier
- 本资源用matlab代码实现了模式识别的线性分类器，对于线性可分的模式能够正确分类。-The resources used matlab code to achieve a pattern recognition linear classifier, for linearly separable model can correctly classified.
three_gram_train
- 直接从文本文档中统计建立三阶语言模型的MATLAB程序-Text document directly MATLAB programs set up third-order statistical language model
lda_perplexity
- 用训练出的模型测试词以及概率，并统计词数和计算困惑度-With the trained model test and the probability and statistics of words, words and perplexity calculation
VAR
- 时域模态分析方法中的多元自回归模型，用于识别结构的模态参数。-Multivariate autoregressive model of time domain modal analysis method, is used to identify structural modal parameters.
LSASummarization-a-paper
- lsasummarization 用 lsa 来干文摘的工作。 配套论文-lsasummarization leverages lsa language model in the task of text summarization
HMM
- Hidden markov model with baum welch algo and vertibi algo
dataobjects
- Dirichlet process mixture model读取数据-Dirichlet read data
UQ-PyL_Linux.tar
- 优化计算程序包,适用于水文及生态模型的优化计算及参数校准。-Uncertainty quantification (UQ) refers to quantitative characterization and reduction of uncertainties present in computer model simulations. It is widely used in engineering and geophysics fields to assess and predict t
6s
- 6s大气传输模型以及用户手册还包括TM实例只需直接输入数据即可-atmosphere transport model,6S,which include manual and some example
HestonCallQuad
- Heston期权定价模型的蒙托卡罗模拟。调用fun函数即可运行-Generalized wave equation parameters of Heston option pricing model Moment Estimation
LSSVM
- 最小二乘支持向量机，程序粘到command window里，设定 2 两个参数，可以更改，以达到最优化-igam=0.001 isig2=0.001 [gam,sig2]=tunelssvm({X,Y, f ,igam,isig2, RBF_kernel },... [0.001 0.001 10000 10000], gridsearch ,{}, leaveoneout_lssvm ) type= function approximation kernel= RBF_
Gmm
- 利用高斯混合模型（gmm）实现了目标与背景的分离以及前景的跟踪。-Gaussian mixture model (gmm) to achieve the objectives and background of the separation and the prospect of tracking.
multiverso-master
- Multiverso is a parameter server based framework for training machine learning models on big data with numbers of machines. It is currently a standard C++ library and provides a series of friendly programming interfaces. With such easy-to-use APIs, m
Example-of-BL-Model
- 金融工程中Black-Litterman模型的R语言代码+案例-Financial engineering R Language Black-Litterman model code+ Case
LDA-topic-model
- 首先声明，这是别人写的LDA主题模型代码，本人测试过，可以运行，但是输出跟输出有点不尽人意，输入的是词的序号和该词在文档中出现的次数，要是可以直接读取文档就完美了。输出是主题以及词在该主题出现的概率，其中得到的主题我就看不懂了，不知道是算法问题，还是因为我的水平有限。在研究LDA主题模型的朋友，可以下载试一下-First statement, which is written by someone else LDA topic model code, I tested, you can run,
Arch Model
- 金融时间序列分析 1. 采用Pandas从Yahoo网上下载上市公司的5到10年的日收盘数据，上证指数的日收盘数据。 2. 计算上市公司和上证指数的收益率， 3. 针对上市公司收益率进行ARMA建模，确定P和q，并对残差进行分析，最后向前预测多期，显示预测图。 4. 针对上市公司收益率进行ARCH建模，确定阶数，并对残差进行分析，最后进行预测。 5. 针对上市公司收益率进行GARCH建模，确定阶数，并对残差进行分析，最后进行预测。(use Arch Model to ananlyse