k-nearest neighbor method 中文意思是什麼

k-nearest neighbor method 解釋
k-最近鄰法
  • k : （pl Ks K s; ks k s ）1 英語字母表第十一字母。2 K字形物體[記號]。3 一個序列中的第十一〈若 J 略去...
  • nearest : ad. 最近的，最親近的
  • neighbor : n 1 鄰人 鄰居；鄰近的人；鄰國（人）。2 鄰座（的人）；鄰接的東西。3 同胞；世人。4 （對任何不知姓名...
  • method : n 1 方法，方式；順序。2 （思想、言談上的）條理，規律，秩序。3 【生物學】分類法。4 〈M 〉【戲劇】...
  1. It discusses three kinds of chinese text caegorizahon methods like bayes method, k nearest neighbor ( knn ) and support vector machines ( svm )

    較全面地討論了貝葉斯方法、 k近鄰方法和支持向量機等三種中文文本分類方法。
  2. When the discount coefficient is 1 and all weights of the nearest neighbor sample points are the same, the k - nn classification method based on evidence reasoning model will become the k - nn classification method based on evidence theory

    並且當折扣系數為1 ，且給定所有最近鄰樣本點權重相等時，基於證據推理模型的k - nn分類方法就成為基於證據理論的k - nn分類方法。
  3. Data mining is defined as the nontrivial extraction of implicit, previously unknown, and potentially useful information from data or known as knowledge - discovery in databases ( kdd ). to do this, data mining uses computational techniques from statistics, machine learning and pattern recognition such as discriminate analysis, regression method, mathematical programming, decision tree, k - nearest neighbor, artificial neural network etc. although many positive attempts are done, the development and application of personal credit assessment model in chinese bank industry is still in its infancy

    數據挖掘是20世紀90年代後期人工智慧和數據庫領域興起的一種數據處理和知識發現（ kdd ）理論，是從大量的、不完全的、有噪聲的、模糊的和隨機的實際應用數據中，提取隱含在其中的信息和知識的過程。對數據進行分類和預測是數據挖掘的主要功能。數據挖掘用於信用評估的優勢主要在於: （ 1 ）能處理和修正實際數據問題，演算法模型具有自檢
  4. The comparative performances are studied among the nmfs + rbf method, the pca + rbf method, and the pca + fld ( fisher ' s linear discriminant ) method. all simulations are carried out on the orl face database. the simulation results show that rbf classifier outperforms k - nearest neighbor linear classifier significantly in recognizing faces with occlusions, and the holistic representations are generally less sensitive to occlusions or noise than parts - based representations

    為了驗證本文所提出的nmfs + rbf演算法的性能，經典的基於pca和fisher線性判別（ fisher ' slineardiscriminant ， fld ）的人臉識別方法，以及基於pca和rbf的人臉識別方法，被用於和本文所提出的人臉識別方法進行比較。
  5. This recognition method integrates traits of nearest neighbor method and k - neighbor method. its basic principle is to improve recognition reliability with tow additive thresholds. in addition, ternary threshold neighbor recognition method ’ s fast arithmetic based on c - average clustering and huffman tree is put forward

    2 .本文在經典統計模式識別方法的基礎上，結合了最近鄰識別法和k近鄰識別法的特點，給出一種三閾值近鄰識別方法，其基本原則是在尋找未知樣本的近鄰時，通過附加閾值的限制，進一步提高識別的可靠性。
  6. In order to reduce the disadvantageous influence of decision profiles ' scattering on fusion recognition, the decision profile is taken as target ' s feature vector and k - nearest neighbor method is applied to classify the target

    為減少目標決策分布圖散布對融合識別效果的影響，提出採用k近鄰方法對目標的決策分布圖進行分類，以實現融合識別。
  7. Then, because of the characteristic of complex engineering systems like fighters, such as modeling difficulty, multiplicity work situations, difficulty and expensiveness for test, a new kind of fast fault predictor is designed based on an improved k - nearest neighbor method, which neither need math model of system nor need data for train and knowledge

    其次，針對殲擊機等復雜工程系統建模困難、工作情況多樣、試驗困難且代價高昂的特點，提出了一種改進k近鄰密度估計方法，設計了一種完全既不需要系統數學模型也不需要故障訓練數據和先驗知識的實時故障預報器。
  8. In this paper, a novel - it composite distance transformation method, which is called cdt, is proposed to support a fast k - nearest - neighbor k - nn search in high - dimensional spaces

    提出一種新型的基於復合距離轉化的索引方法cdt composite distance transformation ，以支持快速的k近鄰查詢。
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