自己花費整整兩個星期寫出來的關(guān)于數(shù)據(jù)挖掘K-means算法的論文，論文中詳細的進行了論述并提出了改進后的算法以及對比歡迎下載
標(biāo)簽： K-means 數(shù)據(jù)挖掘 算法 論文
上傳時間： 2016-01-25
上傳用戶：時代電子小智
vbn gfjhgljl k jhkjo lvbfdghfdhxfgjhkh
標(biāo)簽： lvbfdghfdhxfgjhkh gfjhgljl jhkjo vbn
上傳時間： 2016-01-25
上傳用戶：450976175
This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers using the K-means algorithm. Output is directed to the screen.
標(biāo)簽： code implementing directory algorithm
上傳時間： 2014-01-15
上傳用戶：woshini123456
k-means是一種經(jīng)典的聚類算法，這是用java實現(xiàn)k-means的源碼，其中包括了測試數(shù)據(jù)文件
上傳時間： 2014-01-11
上傳用戶：lizhizheng88
模式識別中K均值算法的示例程序，可對一組數(shù)據(jù)分類并圖形輸出分類結(jié)果。
上傳時間： 2013-12-23
上傳用戶：yph853211
This code implements the shortest path algorithm via the simple scheme and fibonacci heap data structure. It has 3 kinds of testing data input method : random input by computer, reading from the file, reading from the key board.
標(biāo)簽： implements algorithm fibonacci the
上傳時間： 2013-12-23
上傳用戶：ynzfm
How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
標(biāo)簽： the decision clusters Cluster
上傳時間： 2013-12-21
上傳用戶：gxmm
主要是KNN（the k-nearest neighbor algorithm ）,LVQ1（learning vector quantization 1）, DSM（decision surface mapping）算法。 and a simple clustering algorithm.
標(biāo)簽： quantization k-nearest algorithm decision
上傳時間： 2016-02-07
上傳用戶：zhyiroy
這是一個關(guān)于K均值的聚類算法希望對大家有用
上傳時間： 2016-02-15
上傳用戶：ma1301115706
選擇第k小的元素，c語言 partition 要好好看看 理解函數(shù)意思
標(biāo)簽： 元素
上傳時間： 2016-02-19
上傳用戶：ukuk
蟲蟲下載站版權(quán)所有 京ICP備2021023401號-1
