classification error 中文意思是什麼

classification error 解釋
分類誤差
  • classification : n 1 選別；分等，分級；分選。2 【動、植】分類（法）。 〈分類級別為： phylum 【動物；動物學】及 div...
  • error : n. 1. 錯誤；失錯。2. 謬見，誤想；誤信；誤解。3. 罪過。4. 【數學】誤差；【法律】誤審，違法；（棒球中的）錯打。adj. -less 無錯誤的，正確的。
  1. One fault diagnosis model and corresponding algorithm was constructed based on neural network and evidence theory for taking a step forward diagnosis correct rate, which can cut down the imput dimension of neural network 、 improve classification ability 、 decrease the error classify rate of diagnosis system. then, the feasibility and effectiveness of this method was manifested by specific diagnosis example

    為進一步提高診斷準確率，本文基於神經網路和證據理論，構建了基於決策層信息融合的故障診斷模型及其相應演算法，目的在於降低神經網路的輸入空間，提高其分類能力，降低診斷系統的誤分類，診斷實例表明了這種方法的可行性和有效性。
  2. At the other end of the spectrum, high - error - rate ( 4 percent ) random sampling of the genome has proved useful for discovery and classification of various rna and tissue types

    從另一角度來看，對基因組隨機取樣定序，即使誤差高（ 4 % ） ，卻對發現和區分各種rna和組織類型極為有用。
  3. According to principle of reducing recognition error rate, increasing the ability of real - time processing, making the loss least, the multilevel classification mode is selected to classify the stored food insects

    依照降低誤識率、提高實時處理能力以及誤分類損失最小的原則，本文選用了多級分類的方式進行儲糧昆蟲分類。
  4. In the data mining prototype system, apriori algorithm of association rules mining, id3 algorithm of decision tree classification, c4. 5 pessimism estimate algorithm of decision tree classification and c4. 5 reduced - error pruning algorithm of decision tree classification are realized

    在數據挖掘原型系統中，實現了關聯分析的apriori演算法、分類的id3決策樹演算法、 c4 . 5的悲觀估計決策樹演算法和c4 . 5決策樹的消除誤差修剪演算法（ reduced - errorpruning ） 。
  5. It turns out with practical examples that the classification error can be greatly reduced by virtue of rough set theory methodology

    結合實例說明了在聚類分析過程中，可以應用粗糙集方法有效地降低誤分類率。
  6. ( 2 ) an efficient training algorithm for pnn using the minimum classification error criterion is presented

    （ 2 ）提出了一種基於最小分類錯誤準則的概率神經網路的訓練演算法。
  7. Each band of hyperspectral image has the same physical structure, so we classification the first band, and design an optimal linear predictor for each class to make the mean prediction square error minimal, and then we use jpeg - ls algorithm to remove the spatial redundancy

    由於高光譜圖像每個波段都具有相同的物理結構，先對首幅圖像進行分類，在每個子類中分別使用各自的最佳線性預測器，將該類中的相鄰譜段進行預測並將預測殘差均方降為最小，然後用jpeg - ls演算法去除殘差圖像的相關性。
  8. In the stage of training, nntcs applies labeled documents to ann for training, and the error back propagation algorithm ( bp ) is employed to adjust weights of the networks. after training, the final fixed weights are saved as knowledge of classification

    在文本訓練的時候，利用標記好的訓練文檔集進行網路訓練，誤差反饋演算法對網路進行權值調整，得到固定的權值作為分類知識存儲。
  9. Normal behavior and anomaly are distinguished on the basis of observed datum such as network flows and audit records of host. when a training sample set is unlabelled and unbalanced, attack detection is treated as outlier detection or density estimation of samples and one - class svm of hypersphere can be utilized to solve it. when a training sample set is labelled and unbalanced so that the class with small size will reach a much high error rate of classification, a weighted svm algorithm, i

    針對訓練樣本是未標定的不均衡數據集的情況，把攻擊檢測問題視為一個孤立點發現或樣本密度估計問題，採用了超球面上的one - classsvm演算法來處理這類問題;針對有標定的不均衡數據集對于數目較少的那類樣本分類錯誤率較高的情況，引入了加權svm演算法-雙v - svm演算法來進行異常檢測;進一步，基於1998darpa入侵檢測評估數據源，把兩分類svm演算法推廣至多分類svm演算法，並做了多分類svm演算法性能比較實驗。
  10. Based on the analysis of image wavelet transformation and the space / frequency distributing characteristics of different subbands " coefficients, this dissertation fully exploits the following theories and methods : scalar quantization, vector quantization, trellis coded quantization, trellis coded vector quantization, vector classification, codebook expansion and weighted mean square error rule basing mankind visual characteristics, etc. from different angles of information amalgamation, it develops several innovative algorithms of image compression and coding, gives their realization schemes, and makes plentiful simulation tests

    本文在分析了圖像小波變換的原理和子帶系數空間及頻率分佈特點的基礎上，充分利用標量量化、矢量量化、網格編碼量化、網格編碼矢量量化、矢量分類、碼書擴展和基於人眼視覺特性的加權均方誤差準則等思想和方法，從信息融合的不同角度展開了對小波圖像的壓縮編碼研究，同時也討論了這些方法在靜止圖像量化中的具體應用。
  11. The overall accuracy and kappa index are calculated by using the error matrix to check up the classification ’ s accuracy

    為檢驗分類精度，本文使用了誤差矩陣，計算了分類總精度和kappa指數。
  12. The latter classification method combined variable precision rough set model with k - nn classification method, so we can control the classification accuracy rate by the most endurable given error classification rate, then we can make the classification result conform to what we expect, and also some examples are given

    后一種分類方法是將可變精度粗集模型與k - nn分類結合起來，從而可通過給定最大容忍的錯誤分類率來控制分類的準確度，使分類結果達到所期望的目的。並且給出了一些例子。
  13. Different like classical pca, which objects at minimizing the reconstruction error and treats equally each feature, the weighted pca associates each feature with a coefficient according to its role in the recognition task and minimizes the weighted reconstruction error. then classify new samples by calculating the point from weighted subspace distance for classification

    與傳統主元分析不同，加權主元分析根據特徵的分類能力進行加權，通過最小化加權重建誤差來尋找加權子空間，並利用點到加權子空間的距離進行分類。
  14. One major classification of robot visual servoing system distinguishes position - based control form image - based control based on the error signal is defined in 3d coordinates or directly in terms of image features

    目前，機器人視覺伺服系統根據視覺反饋信號表示的是3d空間坐標值或是圖像特徵值而分為基於位置的（ position - based ）和基於圖像的（ image - based ）視覺閉環反饋兩種方式。
  15. Following these, a new global profit tradeoff optimization model based on optimal classification of 1c products is brought forward and its error is estimated

    接著，提出了一種新型的分檔效益協調優化模型，並估計了模型的誤差。
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