资源列表
Read_LibSVM_files_in_R
- Read LibSVM files using R. LibSVM is a MATLAB based library of UCI repository Data Sets. You can convert the data sets to R using this code
DataDemo
- this a data for a small application. the aim of this work is to active my account, tks :D-this is a data for a small application. the aim of this work is to active my account, tks :D
naivebayes
- 朴素贝叶斯算法 求导致某一结果或现象发生的最可能的条件-Naive Bayes algorithm for the most likely cause of the condition or a result of the phenomenon
belajar_decision_tree
- Decision Tree Classifier applied on standard Iris dataset using Python.
Kmeans2_k2
- 对给定的一组数据点采用k均值进行划分，并用散点图表示了出来-A set of data points in a given using k-means partition, and a scatter diagram
LassoBoosting
- lassoBoosting 自己实现的一个小程序，R语言版本的。比较简洁，适合理解这个算法-lassoBoosting own implementation of a small program, R language versions. Relatively simple for understanding the algorithm
Combination_prediction
- 组合预测模型，五个单项模型的组合预测模型和两个单项模型组合的预测模型-Combination forecasting
SVD_EST
- 自行编写的加入噪声估计的KSVD去噪算法，利用SVD分解进行噪声估计- KSVD denoising algorithm to prepare the addition of noise estimation, the use of SVD decomposition noise estimation
Naive-bayes
- 本文以拼写检查作为例子，讲解Naive Bayes分类器是如何实现的。对于用户输入的一个单词（words），拼写检查试图推断出最有可能的那个正确单词（correct）。当然，输入的单词有可能本身就是正确的。比如，输入的单词thew，用户有可能是想输入the，也有可能是想输入thaw。为了解决这个问题，Naive Bayes分类器采用了后验概率P(c|w)来解决这个问题。P(c|w)表示在发生了w的情况下推断出c的概率。为了找出最有可能c，应找出有最大值的P(c|w)，即求解问题-In this
kmeans_cq
- Kmeans算法的简单应用，根据重庆市各区经济情况聚类-Simple application Kmeans algorithm, according to the economic situation in the districts of Chongqing Cluster
LogitTwice
- 基于逻辑回归的二分类算法代码，能很好的实现-Binary logistic regression based algorithm code, can achieve a good
Kmeans
- 直接输入图片，以及类别数，返回分类结果，聚类中心，跌代次数。-Directly enter the picture, as well as the number of categories, the classification result is returned, the cluster center, down the number of generations.