inductive hypothesis 中文意思是什麼
inductive hypothesis
解釋
歸納假設- inductive : adj. 1. 引入的，誘導的 （to）。2. 【邏輯學】歸納的，歸納法的 （opp. deductive）。3. 【電學】感應的，電感的。4. 導論的，緒論的。adv. -ly ,-ness n.
- hypothesis : n. （pl. -ses ）1. 假設；假說。2. 【邏輯學】前提。
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The cause of the goodman paradox is not only the indiscrimination of the law - like hypothesis and accidental hypothesis but also such a characterization : it is unnecessary but improbable that the conclusion is false while the premises are all true ( " inductive probability " )
摘要之所以會產生古德曼悖論，不僅是因為類律假說和偶適假說的混同，而且也是因為對歸納的這樣一個似是而非的刻畫：假設歸納推理的前提都為真，則其結論不一定但很可能為真（即所謂的「歸納概然性特徵」 ） 。 -
Carnap ' s inductive logical system of the theory of probability confirmation is introduced in the second part of paper. firstly, some basical and important concepts are explained such as confirmation and degree of confirmation, probability1 and probability2. in carnap ' s opinion, the difference between verifiability and confirmation is that verifiability means the hypothesis is finally proved to be true, but confirmation means it be true nowerdays. then carnap analyzed the distinction and relationship between probabilityi and probability2
他認為，證實是決定性地最後為真，而確證只是現階段得到確定，並不保證以後也確定為真；繼而分析了概率1與概率2兩者之間的區別與聯系；然後構建了一階語言系統，並在其中定義了狀態描述、結構描述、量程等重要概念與定理，以便使在考察歸納邏輯前提與結論時，能在該系統中根據確切的規則進行準確的分析。 -
The dissertation mainly aims at applying several active machine learning strategies to intrusion detection and systematically studies signal analysis techniques of intrusion detection based on statistical learning theory ( slt ), symbol inductive learning theory and genetic learning method. meanwhile, performance comparison and evaluation among intrusion detection techniques based on different machine learning strategies are presented according to computational learning theory and statistical hypothesis test methodology. intrusion detection is regarded as a pattern recognition problem in term of statistical learning theory ; i
本文的主要工作是將目前幾種有生命力的機器學習策略應用於入侵檢測技術中，論文從入侵檢測的不同視角出發，系統深入地研究了統計學習理論、基於符號的歸納學習理論和遺傳學習方法在入侵檢測信號分析中的應用技術，並在可能近似正確（ pac ）學習框架下，利用計算學習理論和統計假設檢驗方法對基於不同機器學習策略的入侵檢測方法進行了性能比較和評估。
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