搜索资源列表
ann
- 神经网络的R语言程序，有分类的和回归的，可以直接运行-R programming language of neural network, a classification and regression, can be directly run!!!!!
VB-Regular-Demon
- 这是一个利用正则表达式来提取指定数据的VB程序演示，利用正则可以很方便地从一堆杂乱的数据中提取所要的数据，示例中提取的是手机号码，还可以对处理结果进行去除重复的处理，大大加快工作的效率。-This is a use regular expressions to extract VB program demonstrates the specified data, the use of regularization can easily extract the desired data a ju
CalcActivationCode
- 岩土数值模拟计算的程序，可以用来计算边坡、岩石稳定性。-Numerical simulation of geotechnical calculation program can be used to calculate the slope, rock stability.
huadong
- 信号预处理时，需要对信号进行滑动去噪，该程序可以实现滑动去噪，交互友好，我做毕业论文用的。-When the signal preprocessing, the need for signal denoising slide, the program can achieve the sliding de-noising, interactive and friendly, I do thesis use.
Desktop
- K均值聚类算法，对风电机组功率数据进行聚类分析，包括详细的程序说明。 只要把这两个文件放入一个空文件夹下，在MATLAB中执行m文件，就可得到聚类结果。-K-means clustering algorithm, the wind turbine power data clustering analysis, including a detailed descr iption of the procedures. As long as these two files into an empt
SVM_regression_1001
- 一种可以择优选择参数的SVM拟合回归程序，通过for循环，可以调节参数，调出误差最小的参数设置。有时候，默认的参数也会有很不错的精度。-One can choose the best parameters of the SVM fitting regression procedures, through the for cycle, you can adjust the parameters, minimize the error of the parameter settings. Somet
KSVD
- ELAD论文中的KSVD分解标准程序，可对照论文进行理解-ELAD papers in the KSVD decomposition standard procedures, can be controlled to understand the paper
CF
- 这是用matlab写的协同滤波算法主程序，程序简单，易于理解。可以应用于推荐系统-It is used to write collaborative filtering algorithm matlab main program, the program is simple and easy to understand. Recommended system can be applied。。。。。。
svm_python
- 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。本程序是SVM的python实现，用的是SMO算法。只能进行分类，并且能够显示图形结果。-In the field of machine learning, support vector machines SVM (Support Vector Machine) is a supervised learning model is usually use
Bayes
- 本程序是使用的Python写的一个Bayes分类器，通过这个程序可以大致掌握Bayes的原理。-This procedure is used to write a Python Bayes classifier, through this program can be broadly master the principles of Bayes.
DecisionTree
- 本程序是利用python写的一个决策树算法，通过该例子可以实现简单的决策树处理，也可以学习决策树算法的基本思想。-This procedure is to use python to write a decision tree algorithm, this example can be achieved by a simple decision tree processing, you can also learn the basic idea of the decision tree alg
K-means
- 本程序是用python写的一个K均值算法，通过该算法可以学习一python实现算法的流程，以及学习该算法的使用。-The program is written in python a K-means algorithm, the algorithm can learn a python algorithm implementation processes, and learning to use the algorithm.
KNN-implement-by-python
- 该程序是用python编写一个K近邻算法，通过该例子可以掌握K近邻算法，是学习数据挖掘的一个高效的算法。-The program is written in python a K-nearest neighbor algorithm, this example can grasp the K-nearest neighbor algorithm, a learning data mining and efficient algorithms.
AI-Naive
- 利用Python实现朴素贝叶斯分类方法。实现程序具有普适性，同时附带测试数据。可以直接运行。-Python implementations utilizing Naive Bayes classification. Achieve universal program has also included with the test data. It can be run directly.
fastICA
- 快速ICA程序，打开直接进入ICA界面，导入数据即可进行计算-Fast ICA program, open directly into the ICA interface, you can import data to calculate
CalculationSnowfallRainfallRatio2
- 该程序能够最快的对GCM数据进行处理,并能得到好的结果！-The program can be the fastest GCM data processing, and can get good results!
CARS_Characteristic-band-extraction
- 特征带提取算法，可以很好地提取有用的频带，结果更为准确，CARS_Characteristic带提取.m为主程序，调用程序中的压缩包。-Feature band extraction algorithm, can be a good extraction of useful bands, the results are more accurate, CARS_Characteristic band extraction.m for the main program, call the progr
KPCA
- 一个可以直接调用的kpca程序，自己修改的，证明可用的-One can directly call the KPCA program, modify their own, proven available
kmeans
- Kmeans算法的matlab实现，包括主程序和main程序，可运行，易于理解。-Kmeans algorithm matlab implementation, including the main program and the main program can be run, easy to understand.
nmf
- 非负矩阵分解，处理合成孔径雷达图像，数据处理(The multichannel or wide-angle imaging performance of synthetic aperture radar (SAR) can be improved by applying the compressed sensing (CS) theory to each channel or sub-aperture image formation independently.)