文件名称:01DTree
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步骤：
为了判断未知实例的类别，以所有已知类别的实例作为参照
选择参数K
计算未知实例与所有已知实例的距离
选择最近K个已知实例
根据少数服从多数的投票法则(majority-voting)，让未知实例归类为K个最邻近样本中最多数的类别(steps:
In order to determine the unknown instance categories, with examples of all known categories as reference
Parameter selection of K
The calculation examples and all known examples of the unknown distance
Choose the closest known instance K
According to the majority voting rule (majority-voting), for example the unknown classified as K most adjacent to the majority in the sample category)
为了判断未知实例的类别，以所有已知类别的实例作为参照
选择参数K
计算未知实例与所有已知实例的距离
选择最近K个已知实例
根据少数服从多数的投票法则(majority-voting)，让未知实例归类为K个最邻近样本中最多数的类别(steps:
In order to determine the unknown instance categories, with examples of all known categories as reference
Parameter selection of K
The calculation examples and all known examples of the unknown distance
Choose the closest known instance K
According to the majority voting rule (majority-voting), for example the unknown classified as K most adjacent to the majority in the sample category)
相关搜索： 决策树
(系统自动生成,下载前可以参看下载内容)
下载文件列表
01DTree\3.1 决策树(decision tree)算法.html
01DTree\3.1 决策树(decision tree)算法_files\c2cec3fdfc0392456a6ac4258694a4c27d1e2538.jpg
01DTree\3.1 决策树(decision tree)算法_files\Image [1].png
01DTree\3.1 决策树(decision tree)算法_files\Image [2].png
01DTree\3.1 决策树(decision tree)算法_files\Image [3].png
01DTree\3.1 决策树(decision tree)算法_files\Image [4].png
01DTree\3.1 决策树(decision tree)算法_files\Image [5].png
01DTree\3.1 决策树(decision tree)算法_files\Image [6].png
01DTree\3.1 决策树(decision tree)算法_files\Image [7].png
01DTree\3.1 决策树(decision tree)算法_files\Image [8].png
01DTree\3.1 决策树(decision tree)算法_files\Image.png
01DTree\3.1 决策树(decision tree)算法_files\Thumbs.db
01DTree\3.2 决策树(decision tree)应用.html
01DTree\3.2 决策树(decision tree)应用_files\Image.png
01DTree\3.2 决策树(decision tree)应用_files\Thumbs.db
01DTree\allElectronicInformationGainOri.dot
01DTree\AllElectronics.csv
01DTree\AllElectronics.py
01DTree\3.1 决策树(decision tree)算法_files
01DTree\3.2 决策树(decision tree)应用_files
01DTree
01DTree\3.1 决策树(decision tree)算法_files\c2cec3fdfc0392456a6ac4258694a4c27d1e2538.jpg
01DTree\3.1 决策树(decision tree)算法_files\Image [1].png
01DTree\3.1 决策树(decision tree)算法_files\Image [2].png
01DTree\3.1 决策树(decision tree)算法_files\Image [3].png
01DTree\3.1 决策树(decision tree)算法_files\Image [4].png
01DTree\3.1 决策树(decision tree)算法_files\Image [5].png
01DTree\3.1 决策树(decision tree)算法_files\Image [6].png
01DTree\3.1 决策树(decision tree)算法_files\Image [7].png
01DTree\3.1 决策树(decision tree)算法_files\Image [8].png
01DTree\3.1 决策树(decision tree)算法_files\Image.png
01DTree\3.1 决策树(decision tree)算法_files\Thumbs.db
01DTree\3.2 决策树(decision tree)应用.html
01DTree\3.2 决策树(decision tree)应用_files\Image.png
01DTree\3.2 决策树(decision tree)应用_files\Thumbs.db
01DTree\allElectronicInformationGainOri.dot
01DTree\AllElectronics.csv
01DTree\AllElectronics.py
01DTree\3.1 决策树(decision tree)算法_files
01DTree\3.2 决策树(decision tree)应用_files
01DTree
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