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DECISION-Based

Form1.cs是應用聚類算法DBSCAN (Density-Based Spatical Clustering of Application with Noise)的示例

Form1.cs是應用聚類算法DBSCAN (Density-Based Spatical Clustering of Application with Noise)的示例，可以通過兩個參數EPS和MinPts調節聚類。DBSCAN.cs是全部算法的實現文件，聚類算法的進一步信息請參考“數據挖掘”或者相關書籍。聚類示例數據來自于sxdb.mdb，一個Access數據庫。

標簽： Density-Based Application Clustering Spatical

上傳時間： 2015-05-26

上傳用戶：三人用菜
Face recognition eigen-based by Santiago Serrano

Face recognition eigen-based by Santiago Serrano

標簽： recognition eigen-based Santiago Serrano

上傳時間： 2014-11-26

上傳用戶：qweqweqwe
Metalworks is a simple Swing-based simulated e-mail application. It shows off several features of S

Metalworks is a simple Swing-based simulated e-mail application. It shows off several features of Swing, including JInternalFrame, JTabbedPane, JFileChooser, JEditorPane, and JRadioButtonMenuItem. Metalworks is optimized to work with the Java look and feel (codenamed "Metal") and shows use of several features, such as themes, that are specific to the Java look and feel.

標簽： Swing-based application Metalworks simulated

上傳時間： 2015-05-30

上傳用戶：lizhen9880
Expert Choice represents a significant contribution to the decision making process 工t assists a deci

Expert Choice represents a significant contribution to the decision making process 工t assists a decision maker in solving complex problems involving many criteria and several courses of action . An Expert Choice solution to a problem reflects the expertise of the decision maker , not the computer . Behavioral scientists have spent many years studying the human mind and how it makes decisions . They have found that humans are influenced by their previous experiences and this causes them to have biases . Basic instincts , preferences and environmental factors also play key roles in how we analyze data and make decisions . There 15 way to remove these factors from human decision making , nor would we necessarily want to , but as the problems of our world become more and more complex , it 15 necessary for us to employ a framework to help make more logical and less biased decisions while still taking our feelings and intuition into consideration .

標簽： contribution significant represents decision

上傳時間： 2015-06-02

上傳用戶：gmh1314
Frequency Scale Conversion From f To f Scale frq2mel mel2frq mel The mel scale is based on the hu

Frequency Scale Conversion From f To f Scale frq2mel mel2frq mel The mel scale is based on the human perception of sinewave pitch. frq2erb erb2frq erb The erb scale is based on the equivalent rectangular bandwidths of the human ear. frq2midi midi2frq midi The midi standard specifies a numbering of semitones with middle C being 60. They can use the normal equal tempered scale or else the pythagorean scale of just intonation. They will in addition output note names in a character format.

標簽： Scale Conversion Frequency mel

上傳時間： 2015-06-07

上傳用戶：
多階段決策過程（ multistep decision process ）是指這樣一類特殊的活動過程

多階段決策過程（ multistep decision process ）是指這樣一類特殊的活動過程，過程可以按時間順序分解成若干個相互聯系的階段，在每一個階段都需要做出決策，全部過程的決策是一個決策序列。動態規劃（ dynamic programming ）算法是解決多階段決策過程最優化問題的一種常用方法，難度比較大，技巧性也很強。利用動態規劃算法，可以優雅而高效地解決很多貪婪算法或分治算法不能解決的問題。動態規劃算法的基本思想是：將待求解的問題分解成若干個相互聯系的子問題，先求解子問題，然后從這些子問題的解得到原問題的解；對于重復出現的子問題，只在第一次遇到的時候對它進行求解，并把答案保存起來，讓以后再次遇到時直接引用答案，不必重新求解。動態規劃算法將問題的解決方案視為一系列決策的結果，與貪婪算法不同的是，在貪婪算法中，每采用一次貪婪準則，便做出一個不可撤回的決策；而在動態規劃算法中，還要考察每個最優決策序列中是否包含一個最優決策子序列，即問題是否具有最優子結構性質。

標簽： multistep decision process 過程

上傳時間： 2015-06-09

上傳用戶：caozhizhi
Based on 80C196MC One-chip Computer Frequency Conversion Rapid System of Accent Design Program Listi

Based on 80C196MC One-chip Computer Frequency Conversion Rapid System of Accent Design Program Listing

標簽： Conversion Frequency Computer One-chip

上傳時間： 2015-06-11

上傳用戶：我們的船長
gaussian_model,color based segmentation,draw ellipse may used in face detection

gaussian_model,color based segmentation,draw ellipse may used in face detection

標簽： gaussian_model segmentation detection ellipse

上傳時間： 2015-06-13

上傳用戶：yuchunhai1990
color based segment in YCbCr space

color based segment in YCbCr space

標簽： segment color based YCbCr

上傳時間： 2015-06-13

上傳用戶：84425894
The EM algorithm is short for Expectation-Maximization algorithm. It is based on an iterative optimi

The EM algorithm is short for Expectation-Maximization algorithm. It is based on an iterative optimization of the centers and widths of the kernels. The aim is to optimize the likelihood that the given data points are generated by a mixture of Gaussians. The numbers next to the Gaussians give the relative importance (amplitude) of each component.

標簽： algorithm Expectation-Maximization iterative optimi

上傳時間： 2015-06-17

上傳用戶：獨孤求源