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Description: 使用SVM支持向量机 预测分类
使用SVM支持向量机 预测分类-use SVM SVM forecast classification SVM SVM classification forecast
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Size: 1853 |
Author: 林尚义 |
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Description: 使用SVM支持向量机 预测分类
使用SVM支持向量机 预测分类-use SVM SVM forecast classification SVM SVM classification forecast
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Size: 2048 |
Author: 林尚义 |
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Description: SVMhmm: Learns a hidden Markov model from examples. Training examples (e.g. for part-of-speech tagging) specify the sequence of words along with the correct assignment of tags (i.e. states). The goal is to predict the tag sequences for new sentences.
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Size: 95232 |
Author: 王强 |
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Description: 这个程序是matlab编写的支持向量程序，主要由于预测。-This procedure is prepared matlab support vector procedure, mainly due to prediction.
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Size: 425984 |
Author: mawenguo |
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Description: 支持向量机算法预测部分，主要是针对大规模对象进行预测-Support Vector Machine forecast, mainly for large-scale objects to predict
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Size: 2048 |
Author: 张怡 |
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Description: 支持向量机用于回归预测的部分，功能强大又简单容易理解，用于模式识别的好工具-Parts of SVM for predict,gteat function and easy to understand, a good machine for classification
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Size: 2048 |
Author: susuxuan |
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Description: SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
-SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X--> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
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Size: 109568 |
Author: jon |
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Description: SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
-SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X--> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
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Size: 117760 |
Author: jon |
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Description: SVM神经网络的信息粒化时序回归预测----上证指数开盘指数变化趋势和变化空间预测-Information Granular SVM neural network time series regression of the Shanghai Composite Index opened---- Index forecast trends and changes in space
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Size: 223232 |
Author: eason |
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Description: 支持向量机来分析数据，并通过建立向量机来预测数据的趋势-Support vector machine to analyze data and predict trends in the data
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Size: 5120 |
Author: jirsin |
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Description: 支持向量机模型用于预测分析效果显著，它在解决小样本、非线性及高维模式识别中表现出许多特有的优势，并能够推广应用到函数拟合等其他机器学习问题中-Support vector machine model is used to predict significant effect in solving small sample, nonlinear and high dimensional pattern recognition exhibit many unique advantages, and be able to promote the application to function fitting machine learning problem
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Size: 1024 |
Author: 伊燕平 |
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Description: 支持向量机源代码,svm预测,使用libsvm进行分类,优化libsvm的各种参数-svm predict
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Size: 1024 |
Author: caoyong |
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Description: SVM神经网络的信息粒化时序回归预测 遗传算法的典型实例-SVM neural network information granulation typical examples of the time series regression to predict genetic algorithm
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Size: 404480 |
Author: 冯翔 |
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Description: 基于svm的一维信号的回归预测，精确度优于传统的神经网络方法-The one-dimensional signal based svm regression prediction accuracy is better than traditional neural network method
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Size: 1024 |
Author: rengailing |
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Description: 基于libSVM-v310的完全多线程化libSVM，仅读写文件在框架内无法优化。svm-predict不需要openmp支持，svm-train需要打开openmp支持。VS2008编译。修改MAX_THREAD可以调整svm-predict线程数。-A fully multi-thread optimized libSVM based on libsvm-3.10. svm-predict won t need openmp however svm-train requires. The project is under VS2008. Please modify MAX_THREAD value to adjust predict threads.
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Size: 20480 |
Author: |
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Description: 一个matlab例程，基于SVM的信息粒化时序回归预测demo，实现了对上证开盘指数变化趋势和变化空间预测-
A matlab routine, regression forecasting demo SVM-based information granulated timing to achieve the opening of the Shanghai index trends and changes in spatial prediction
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Size: 1435648 |
Author: 张竞成 |
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Description: 使用支持向量机算法对二分类问题进行预测，实现大数据分析的目标。(Support vector machine algorithm is used to predict the two classification problem, and achieve the goal of large data analysis.)
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Size: 1024 |
Author: 小麦呀
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Description: SVM处理图像 数据与处理 特征提取 训练模型 模型预测 得到结果(SVM processing image data and processing feature extraction training model model to predict the results)
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Size: 1024 |
Author: 明吗
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Description: 用SVM做预测的matlab程序,内部程序详细，包含数据(a program to predict time series)
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Size: 5120 |
Author: 爱笑的蓝蜗牛
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Description: 利用LibSVM以及SVM模型进行文本数据分类。训练数据与测试数据都有。(Using LibSVM and SVM model to classify text data. Both the training data and the test data are available.)
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Size: 348160 |
Author: 云中漫步xjr |
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