tree label 中文意思是什麼
tree label
解釋
樹名標鑒-
Decision tree is often applied for predicting the class label of data objects and regression model is usually applied in the course of linear problem
決策樹通常用於預測數據對象的類標識,而回歸問題經常解決線性問題。 -
Neural network makes label elements of filter dom tree as input, extract results as output, training via bp learning arithmetic
神經網路將樣本集中過濾后的dom樹的標簽元素作為網路的輸入,標注抽取結果作為理想輸出,通過反向傳播學習演算法對網路進行訓練。 -
The algorithm transforms the traditional tree - to - tree correction into the comparing of the key trees, which are substantially label trees without duplicate paths. thus, the algorithm achieves high efficiency with the complexity of o ( n ), where n is the total number of nodes in the trees, which is significant to the large scaled applications
為適應大規模應用的需要,本文提出了直接利用特徵路徑進行文檔比較的kf - diff +演算法,同時適于有序和無序兩種模式,在時間復雜度上從先前的o ( nlogn )提高到o ( n ) ,更加適合internet規模的應用。 -
Occurs after the tree node label text is edited
在編輯樹節點標簽文本后發生。 -
In building fuzzy decision tree, each expanded attribute ca n ' t classify the class label clearly like decision tree, but the cases covered with the attribute - values have some overlap. so the entire process of building trees is based on a significant level a, the import of a can reduce such overlap in some degree, decrease the uncertainty of classification and improve classification result
在模糊決策樹的產生過程中,用模糊熵選擇的擴展屬性不能像經典決策樹那樣將類清晰的分開,而是屬性術語所覆蓋的例子之間有一定的重疊,因此樹的整個產生過程在給定的顯著性水平的基礎上進行,參數的引入能在一定程度上減少這種重疊,從而減少分類的不確定性,提高模糊決策樹的分類結果。
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