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關注：1
2013-05-23 12:21
求翻譯：對相關數據進行預處理，所有指標進行一致化與無量綱化處理，使用三倍標準差檢驗法進行異常數據的剔出，最終獲得xx個樣本數據，將這xx個樣本劃分為訓練樣本和測試樣本，隨機抽取35%(33個)作為訓練樣本集，用于構造SVMs集成模型，其余的65%(60個)作為測試樣本集，用于模型泛化能力的檢驗。對于可持續發展能力的評價集中，本文采用模糊集來定義輸出級集合，充分結合該領域專家的經驗，將其分成三個等級：可持續發展性強(Ⅰ)、可持續發展性一般(Ⅱ)、可持續發展性弱(Ⅲ)。是什么意思？ 待解決
 懸賞分：1
- 離問題結束還有
對相關數據進行預處理，所有指標進行一致化與無量綱化處理，使用三倍標準差檢驗法進行異常數據的剔出，最終獲得xx個樣本數據，將這xx個樣本劃分為訓練樣本和測試樣本，隨機抽取35%(33個)作為訓練樣本集，用于構造SVMs集成模型，其余的65%(60個)作為測試樣本集，用于模型泛化能力的檢驗。對于可持續發展能力的評價集中，本文采用模糊集來定義輸出級集合，充分結合該領域專家的經驗，將其分成三個等級：可持續發展性強(Ⅰ)、可持續發展性一般(Ⅱ)、可持續發展性弱(Ⅲ)。
問題補充： |
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2013-05-23 12:21:38
Pre-processing of data, all indicators of the same treatment with the non-dimensional, three times the standard deviation using the test method for abnormal data bound, ultimately, xx sample data, this xx samples into training and test samples samples, randomly selected 35% (33) as the training set,
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2013-05-23 12:23:18
The relevant data for pre-processing, all of the indicators for the homogenization and dimensionless quantities of 3 times, use standard deviation of the test for data anomalies, which was ultimately removed from the sample data, xx xx samples which will be divided into training and test samples, ra
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2013-05-23 12:24:58
正在翻譯，請等待...
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2013-05-23 12:26:38
On related data for pretreatment, all indicators for consistent of and non outline of of processing, using three times times standard difference inspection method for exception data of ruled out, eventually get XX a samples data, will this XX a samples Division for training samples and test samples,
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2013-05-23 12:28:18
Pre-processing of data, all indicators of the same treatment with the non-dimensional, three times the standard deviation using the test method for abnormal data bound, ultimately, xx sample data, this xx samples into training and test samples samples, randomly selected 35% (33) as the training set,
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