您要查找的是不是：
- stochastic decision tree analysis 隨機決策樹(shù)分析
- Decision tree is a useful method of classification. 摘要決策樹(shù)是分類(lèi)的常用方法。
- A decision tree is a graphic model of a decision process. 決策樹(shù)是描述決策過(guò)程的一種圖形。
- In the Grid pane, click Source and then select TM Decision Tree mining model. 在“網(wǎng)格”窗格中,單擊“源”,然后選擇“TM Decision Tree挖掘模型”。
- Click Select Model, expand Targeted Mailing, and then choose TM Decision Tree. 單擊“選擇模型”,展開(kāi)“目標郵件”,再選擇TM Decision Tree。
- This viewer contains two tabs, Decision Tree and Dependency Network. 此查看器包含兩個(gè)選項卡,即“決策樹(shù)”和“相關(guān)性網(wǎng)絡(luò )”。
- Evolutionary decision tree method has the advantage of global search. 演化決策樹(shù)方法將傳統的決策樹(shù)算法與演化算法相結合,具有全局搜索的優(yōu)點(diǎn)。
- Decision trees can be used for prediction. 決策樹(shù)可用于進(jìn)行預測。
- Decision tree, neural networks and Bayesian networks are the main tools of KDD. 決策樹(shù)、神經(jīng)網(wǎng)絡(luò )、Bayesian網(wǎng)絡(luò )等是當前知識發(fā)現的重要工具。
- For example, in a decision tree mining model the viewer will use Cyan to display continuous attributes. 例如,在樹(shù)挖掘模型中,查看器將使用青色來(lái)顯示連續屬性。
- On the Decision Tree tab, you can examine all the tree models that make up a mining model. 在“決策樹(shù)”選項卡上,可以檢查構成挖掘模型的所有樹(shù)模型。
- When you build a decision tree model, Analysis Services builds a separate tree for each predictable attribute. 生成決策樹(shù)模型時(shí),Analysis Services將為每個(gè)可預測屬性生成一個(gè)單獨的樹(shù)。
- Now there are many methods that has been applied to this field, such as SVM, KNN, Naive Bayes, Decision Tree, etc. 目前已經(jīng)有許多方法應用到該領(lǐng)域。 如支持向量機方法(SVM)、K近鄰方法(KNN)、樸素貝葉斯方法(Naive Bayes)、決策樹(shù)方法(Decision Tree)等等。
- The traditional decision tree category methods(such as:ID3,C4.5) are effective on small data sets. 傳統的決策樹(shù)分類(lèi)方法(如ID3和C4.;5)對于相對小的數據集是很有效的。
- This paper regards decision tree as basic classifier, and introduces the least square technology for linear fusion. 以決策樹(shù)作為基本分類(lèi)器，引入最小二乘技術(shù)進(jìn)行多分類(lèi)器線(xiàn)性融合。
- One of the best ways to analyze a decision is to use so-called decision trees. 所謂決策樹(shù)是進(jìn)行決策分析的最佳方法之一。
- Two methods for text categorization fuzzy rule extraction are presented based on fuzzy decision tree. 本文提出了兩種基于模糊決策樹(shù)的模糊文本分類(lèi)規則抽取方法。
- Binary decision tree is used to analyze pressing line of vehicles to improve the reliability of the system. 通過(guò)二叉決策樹(shù)來(lái)分析車(chē)輛的壓線(xiàn)過(guò)程，提高了車(chē)流量檢測的可靠性；
- Characteristic Properties of Perspective Sets for Finite Stochastic Decision 有限隨機性決策中展望的特征性質(zhì)
- How to construct the Decision Trees with high precision and small size is core. 如何構造精度高、規模小的決策樹(shù)是決策樹(shù)算法的核心內容。
