Classification Tree Algorithm的意思|示意

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分类树算法


Classification Tree Algorithm的网络常见释义

分类树算法 分类树算法(Classification Tree Algorithm) 分类树(又称判定树, decision tree) 是一种自 上而下递归地对数据进行分割的算法。

Classification Tree Algorithm相关短语

1、 Decision tree classification algorithm 决策树分类算法

2、 classification tree integration algorithm 分类树集成算法

3、 classification and regression tree algorithm 分类和递归树算法

Classification Tree Algorithm相关例句

Compared with the classical ID3 algorithm through an example, the former can reduce the decision tree at the same time of making sure of improving classification accuracy in some certain problem.

通过实例将前向决策树算法与经典的ID 3算法进行了比较,结果表明针对某些特定的问题前者在保证分类精度不降低的同时也简化了决策树。

Meanwhile it describes the decision tree classification algorithm in detail, analyzes the ID3, C4.5 and other prevalent decision tree algorithm.

同时详细的阐述了决策树分类算法,并对比较流行的决策树算法id3、C4.5等算法进行详细分析与比较。

Decision tree algorithms are applied to the data mining of the mammography classification, proposes a medical images classifier based on decision tree algorithm, the experiment results are given.

利用决策树算法对乳腺癌图像数据进行分类,实现了一个基于决策树算法的医学图像分类器,获得了分类的实验结果。

Randomized tree is a supervised classification algorithm for pattern recognition, which can be effectively used in augmented reality feature recognition and matching.

随机树分类算法是一种有监督学习的模式识别分类算法,可有效地应用于增强现实系统中的特征识别与匹配。

There are many classification methods to forecast such as decision tree algorithm (C4.5), Bayes algorithm, BP algorithm and SVM.

现有的分类预测的方法有许多种,常见的有决策树算法(C4.5)、贝叶斯分类算法、BP算法与支持向量机等。

According to these two algorithms, this thesis proposed a new gene function classification algorithm based on gene function tree.

依据这两个准则,本文提出了一种改进的基于基因功能树的基因功能分类算法。