Description: 一个用java写的回归分析的类，可用于预测、模式识别-write with a regression analysis of the category, can be used to predict, pattern recognition Platform: |
Size: 3072 |
Author:雷天无 |
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Description: 成本预测系统，采用二次线形回归模型，采用access数据库，也属于人工智能的领域-Cost prediction systems, using quadratic linear regression model, using access database, but also belong to the field of artificial intelligence Platform: |
Size: 121856 |
Author:zhangxinjie |
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Description: 使用线性回归的方法对股市短期走势作出预测的程序， 基于matlab， 请大家尝试-Using a linear regression method to predict the trend of the stock market short-term process, based on matlab, please try Platform: |
Size: 116736 |
Author:ycs |
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Description: （回归分析）
考察温度x对产量y的影响，测得下列10组数据：
求y关于x的线性回归方程，检验回归效果是否显著，并预测x=42℃时产量的估值及预测区间（置信度95 ）
-(Regression analysis) x on the output of the temperature study of the impact of y, measured the following 10 sets of data: for y on x of the linear regression equation to test whether the effect of a significant regression and prediction when x = 42 ℃, and the valuation of yield prediction interval (95 percent confidence level) Platform: |
Size: 25600 |
Author:mazhen |
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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: 模糊——支持向量机，用于模糊理论与支持向量机结合，用于数据预测-Fuzzy- support vector machines for fuzzy theory and support vector machines for data predict Platform: |
Size: 293888 |
Author:rhz |
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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 Platform: |
Size: 223232 |
Author:eason |
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Description: What for Linear regression is used?
We can predict one variable from another
Y = a+ bX
b = slope a = intercept (constant )
Correlation Coefficient (r) :
A measure of association between two variables.
-What for Linear regression is used?
We can predict one variable from another
Y = a+ bX
b = slope a = intercept (constant )
Correlation Coefficient (r) :
A measure of association between two variables.
Platform: |
Size: 679936 |
Author:Fitrie |
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Description: 有导师学习神经网络的回归拟合——基于近红外光谱的汽油辛烷值预测-Supervised learning neural network regression- based on the gasoline octane number of the near-infrared spectroscopy to predict Platform: |
Size: 173056 |
Author:yanjie |
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Description: C#中的线性回归实现，可以用于函数分析，可对散点函数进行延伸，预测后续点的位置-C# implementation of the linear regression can be used for function analysis, may scatter function extends predict subsequent location of the point Platform: |
Size: 46080 |
Author:hc |
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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 Platform: |
Size: 1024 |
Author:rengailing |
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Description: 支持向量机除了可以进行分类预测还可以进行回归预测，源代码为使用支持向量进行回归预测。-In addition to SVM classification can also be predicted regression prediction, the source code for the use of support vector regression to predict. Platform: |
Size: 3072 |
Author:derekddong |
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Description: 支持向量机除了可以进行分类预测还可以进行回归预测，源代码为使用支持向量进行回归预测。-In addition to SVM classification can also be predicted regression prediction, the source code for the use of support vector regression to predict. Platform: |
Size: 218112 |
Author:yanudinpro |
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Description: 在回归分析中，如果有两个或两个以上的自变量，就称为多元回归。事实上，一种现象常常是与多个因素相联系的，由多个自变量的最优组合共同来预测或估计因变量，比只用一个自变量进行预测或估计更有效，更符合实际。因此多元线性回归比一元线性回归的实用意义更大。-In regression analysis, if there are two or more independent variables, it is called multiple regression. Indeed, a phenomenon often associated with a plurality of factors, from the optimal combination of a plurality of common variables to predict or estimate a dependent variable, compared with only one independent variable to predict or estimate more effective and practical. Multiple linear regression and therefore the practical significance of a linear regression greater. Platform: |
Size: 2048 |
Author:黄毅 |
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Description: 基于Logstic回归分析，建立人口预测模型，对人口数量进行预测-Based Logstic regression analysis, population forecasting model to predict population Platform: |
Size: 50176 |
Author:王旭 |
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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 Platform: |
Size: 1435648 |
Author:张竞成 |
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Description: 对于大盘指数的有效预测可以为从整体上观测股市的变化提供强有力的信息，所以对于上证指数的预测具有很大意义。本代码用Matlab对1990.12.20-2009.8.19-每天的开盘指数进行支持向量机回归分析，拟合效果较好。-For effectively predict the market index can provide a strong message to the observed changes in the stock market as a whole, so the forecast for the Shanghai Composite Index has great significance. The code in Matlab opening day of 1990.12.20-2009.8.19- index support vector machine regression fit better. Platform: |
Size: 2048 |
Author:李凤 |
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Description: 根据已有关于某事物的相关数据，通过此线性回归算法，对事物的发展进行预测，最大程度贴近事实情况。-According to the existing data on something by the linear regression algorithm to predict the development of things, close to the maximum extent the factual circumstances. Platform: |
Size: 1024 |
Author:朱津乐 |
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Search - regression predict