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.
標簽： the decision clusters Cluster
上傳時間： 2013-12-21
上傳用戶：gxmm
ARM7 LED shift register (ST2221) in C programming
標簽： programming register shift ARM7
上傳時間： 2016-02-15
上傳用戶：gtf1207
一個聚類算法用K-mean處理后迭代，論文發表在PAK
上傳時間： 2013-12-09
上傳用戶：66666
This program simulates plant identification least mean square (NLMS) alogrithm reference: 《LMS算法的頻域快速實現》
標簽： identification alogrithm simulates reference
上傳時間： 2013-12-17
上傳用戶：kristycreasy
This program simulates plant identification using frequency block least mean square (FBLMS) alogrithm reference: 《LMS算法的頻域快速實現》 LMS is modified by XXX in XXX place, see details in XXX relevant document
標簽： identification frequency simulates alogrith
上傳時間： 2016-02-29
上傳用戶：kytqcool
Generate 100 samples of a zero-mean white noise sequence with variance , by using a uniform random number generator. a Compute the autocorrelation of for . b Compute the periodogram estimate and plot it. c Generate 10 different realizations of , and compute the corresponding sample autocorrelation sequences , and . Compute the average autocorrelation sequence as and the corresponding periodogram for . d Compute and plot the average periodogram using the Bartlett method. e Comment on the results in parts (a) through (d).
標簽： zero-mean Generate sequence variance
上傳時間： 2016-03-04
上傳用戶：朗朗乾坤
Analysis of PHY waveform Peak to Mean Ratio and Impact on RF Amplification
標簽： Amplification Analysis waveform Impact
上傳時間： 2014-01-15
上傳用戶：hgy9473
k-mean算法演示，利用手工輸入點通過k類自動聚合
上傳時間： 2016-04-09
上傳用戶：shanml
c-mean聚類算法源代碼，通過對輸入數據進行訓練和分類類別設定，能夠得到數據的聚類圖。
上傳時間： 2013-12-26
上傳用戶：colinal
k－mean算法的源碼，對聚類非常有用！！可以直接使用！
上傳時間： 2016-04-21
上傳用戶：ZJX5201314
