Description: K近邻分类器，实现了对iris数据集的分类，并且使用了交叉验证的方法，来验证求得的最优的K值。-K-nearest neighbor classifier to achieve the classification of iris data set and cross-validation of the method used to verify the optimal value of K obtained. Platform: |
Size: 2048 |
Author: |
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Description: 属于机器学习的范畴，通过输入训练样本，通过分类或线性回归得到标签的假设性函数-The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, C++ machine learning library that has been specifically designed for real-time gesture recognition.
In addition to a comprehensive C++ API, the GRT now also includes an easy-to-use graphical user interface (GUI) which enables user s to stream real-time data into the GUI via the Open Sound Control network protocol. Using the GUI you can:
(1) Setup and configure a gesture recognition pipeline that can be used for classification, regression, or timeseries analysis.
(2) Stream real-time data into the GUI via Open Sound Control (OSC) another application (such as Processing, Max, Pure Data, Openframeworks, etc.).
(3) Record, label, save and load your training data.
(4) Train a model for classification or regression.
(5) Test the generalization abilities of the model (using another test dataset or cross validation).
(6) Perform real-time prediction on new data streamed into the GUI via OSC.
(7) Stre Platform: |
Size: 21445632 |
Author:王哲 |
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Description: 单因变量偏最小二乘回归matlab程序
程序尚不完善，固定提取了3个主成分，没有做寻求最佳主成分个数；没有做交叉有效性检验
-Single dependent variable and partial least squares regression matlab
The program is not perfect, the fixed extract 3 principal components, do not seek the best number of principal components do not cross validation test Platform: |
Size: 1024 |
Author:mali |
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Description: 基于Fisher准则多分类特征提取，投影后采用最近邻算法和一对一投票法进行分类和交叉验证，附上数据实例-After feature extraction based on Fisher criterion with multicalsses, the projections are discriminated ultilizing the nearest neighbor algorithm and one-versus-one ballot to have a cross validation Platform: |
Size: 6575104 |
Author:zhangyuan |
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Description: 支持向量机工具箱By Kris De Brabanter,标准的非参数回归，健壮的回归，一些调优标准等经典交叉验证，较好的交互性-The StatLSSVM toolbox is written so that only a few lines of code are necessary in order to perform standard nonparametric regression, regression with correlated errors and robust regression. In addition, construction of additive models and pointwise or uniform confidence intervals are also supported. A number of tuning criteria such as classical cross-validation, robust cross-validation and cross-validation for correlated errors are available. Also, minimization of the previous criteria is available without any user interaction. Platform: |
Size: 326656 |
Author:李杰 |
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Description: 通过KNN分类法，根据酒的某些性状信息对酒进行分类。然后，通过交叉验证对分类结果进行测试。最后，对数据进行主成分分析，再进行分类。-By KNN classification, according to certain traits information wine wine classification. Then, through cross-validation of the classification tested. Finally, principal component analysis of the data, and then classified. Platform: |
Size: 7168 |
Author:王伟 |
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Description: 基于交叉验证的支持向量机算法，程序内可实现选择最佳参数，并对输入数据分类输出-Cross-validation based on support vector machine algorithm, can be realized within the program to the best parameters, and input data classification output Platform: |
Size: 2048 |
Author:duncon |
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Description: 基于Python的贝叶斯实现，同时包含改进贝叶斯算法，同时采用采用留存交叉验证进行验证。-Python-based Bayesian implementations, including improved Bayesian algorithm, while using cross-validation using retained for verification. Platform: |
Size: 3072 |
Author:刘蕾 |
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Description: 交叉验证法寻优的支持向量机突水预测模型，带突水原始数据库-Support vector machine prediction model of water inrush optimization of cross-validation with water inrush original Platform: |
Size: 2048 |
Author:lu bin |
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Description: feather_stacker主要用于一个数据集提取多个特征时，对特征进行联合的算法。-In many real-world examples, there are many ways to extract features a dataset. Often it is beneficial to combine several methods to obtain good performance. This example shows how to use FeatureUnion to combine features obtained by PCA and univariate selection.
Combining features using this transformer has the benefit that it allows cross validation and grid searches over the whole process.
The combination used in this example is not particularly helpful on this dataset and is only used to illustrate the usage of FeatureUnion. Platform: |
Size: 1024 |
Author:申鹏 |
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Description: 实现机器学习（machine learning）中的交叉验证（cross validation）的代码
本身是在相关的toolbox中可以直接使用的function，但是对于没有下载toolbox的朋友，可以使用这个代码-This code is used to conduct cross validation in machine learning.
It is a function which can be directly utilized if you have downloaded the related toolbox. If not, you can use the function in this code. Platform: |
Size: 4096 |
Author:Howard Lee |
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Description: Code for Deep Learning for Detecting Robotic Grasps.Intended to be a simple codebase which will allow you to load the grasping
dataset, process and whiten it, train a network, and perform grasp
detection. Currently does not contain more advanced uation code
(cross-validation, scoring, etc.), or code for the two-pass system
I add dropout to this code.-Code for Deep Learning for Detecting Robotic Grasps.Intended to be a simple codebase which will allow you to load the grasping
dataset, process and whiten it, train a network, and perform grasp
detection. Currently does not contain more advanced uation code
(cross-validation, scoring, etc.), or code for the two-pass system
I add dropout to this code. Platform: |
Size: 19165184 |
Author:youmei Zhang |
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Search - cross validation