discovery method of learning 中文意思是什麼

discovery method of learning 解釋
探討式學習法
  • discovery : n. 1. 發見，發現，發覺。2. 〈古語〉顯示，暴露，顯露。3. （劇情的）發展。4. 被發現的事物。5. 【法律】（審判前當事一方必須作出的）顯示證據。
  • 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】...
  • of : OF ＝Old French 古法語。
  • learning : n 學，學習；學問，學識；專門知識。 good at learning 善於學習。 a man of learning 學者。 New learn...
  1. Considering the one - sidedness and inaccuracy of knowledge discovery only from single - color database, an approach is proposed to discover knowledge from 1331 groups of mix - color database with partial least - square regression, based on measuring and learning 400 groups of single - color database. by this method, the mean error decreases when converting from rgb to cmyk, the precision of color matching is improved, and the automatic and general problem in color matching is further solved

    本文基於統計學習理論構造了一種快速自適應隨機搜索演算法，證明了演算法的收斂性.給出了一種簡易實用的寬帶天線匹配設計新方法.應用該自適應演算法進行天線匹配設計，不僅演算法簡單，易於編程實現;而且能夠快速設計出具有較好性能的匹配網路，非常適用於各種短波、超短波天線的匹配設計問題
  2. One method was supervised recognition, which was to take advantage of some known information to determine a given sequence whether contained some specific functional elements ; the other way was unsupervised learning, which was to utilize some measures of comparability and some search algorithm to discovery some potential signals in biosequences

    一種是有指導的識別方法，即利用已知的信息判讀一段未知的序列中是否含有某種功能元件;另一種是無指導的學習方法，即利用一些相似性指標，通過搜索演算法發現序列中可能蘊含的信號。
  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 more work was to study learning and rule discovery theory of agent by applying the improved michigan method, and to analyze the method of agents how to gain the knowledge belief in the multi - agent environment in virtue of the multi - person game theory, as well as study the game tree structure of the agent ' s belief - desire - intention ( bdi ) model and agent how to decide

    應用改進的密歇根法研究了主體的學習和規則發現的理論與應用，同時藉助多人博弈結構理論，分析了主體在多主體環境下知識信念的獲取方法，以及主體bdi模型的博弈樹結構和主體決策機制。
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