文件名称:DM4
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执行流程：
1. 用户输入参数：K的选择，训练数据，测试数据的路径；
2. 读取训练数据集和测试数据集文件，用ArffFileReader类读取并组织起InstanceSet数据结构；
3. 利用上面的相似度量标准，对每一个测试集中的Instance，计算与其最相似的K个训练集中的Instance，通过投票进行分类，将分类结果存储经Instance的成员变量targetGuess中；
4. 对分类结果进行度量，包括分类正确率，各种类别实例的Precision，Recall；Confusion Matirx；
-Implementation process: 1. User input parameters: K' s choice, the training data, test data path 2. To read the training data set and test data sets document, read and use ArffFileReader category InstanceSet organize the data structure 3. The use of the above similarity metrics for each concentration of a test Instance, the calculation of the K most similar training focused Instance, by voting for classification, the classification results stored by a member of Instance variables in targetGuess 4. on the classification results of measurement, including the classification accuracy of various types of examples of Precision, Recall Confusion Matirx
1. 用户输入参数：K的选择，训练数据，测试数据的路径；
2. 读取训练数据集和测试数据集文件，用ArffFileReader类读取并组织起InstanceSet数据结构；
3. 利用上面的相似度量标准，对每一个测试集中的Instance，计算与其最相似的K个训练集中的Instance，通过投票进行分类，将分类结果存储经Instance的成员变量targetGuess中；
4. 对分类结果进行度量，包括分类正确率，各种类别实例的Precision，Recall；Confusion Matirx；
-Implementation process: 1. User input parameters: K' s choice, the training data, test data path 2. To read the training data set and test data sets document, read and use ArffFileReader category InstanceSet organize the data structure 3. The use of the above similarity metrics for each concentration of a test Instance, the calculation of the K most similar training focused Instance, by voting for classification, the classification results stored by a member of Instance variables in targetGuess 4. on the classification results of measurement, including the classification accuracy of various types of examples of Precision, Recall Confusion Matirx
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下载文件列表
2008212560-2008212552-DM4/readme.txt
2008212560-2008212552-DM4/可执行程序/dataset/soybean-large-test.arff
2008212560-2008212552-DM4/可执行程序/dataset/soybean-large-train.arff
2008212560-2008212552-DM4/可执行程序/knn.bat
2008212560-2008212552-DM4/可执行程序/myKNN.jar
2008212560-2008212552-DM4/源代码/core/Attribute.java
2008212560-2008212552-DM4/源代码/core/Instance.java
2008212560-2008212552-DM4/源代码/core/InstanceSet.java
2008212560-2008212552-DM4/源代码/core/KNNcore.java
2008212560-2008212552-DM4/源代码/core/Target_Simil_Node.java
2008212560-2008212552-DM4/源代码/evaluate/Evaluate.java
2008212560-2008212552-DM4/源代码/file/ArffFileReader.java
2008212560-2008212552-DM4/源代码/util/MainDriver.java
2008212560-2008212552-DM4/源代码/util/QuickSort.java
2008212560-2008212552-DM4/设计及说明文档.docx
2008212560-2008212552-DM4/可执行程序/dataset
2008212560-2008212552-DM4/源代码/core
2008212560-2008212552-DM4/源代码/evaluate
2008212560-2008212552-DM4/源代码/file
2008212560-2008212552-DM4/源代码/util
2008212560-2008212552-DM4/可执行程序
2008212560-2008212552-DM4/源代码
2008212560-2008212552-DM4
2008212560-2008212552-DM4/可执行程序/dataset/soybean-large-test.arff
2008212560-2008212552-DM4/可执行程序/dataset/soybean-large-train.arff
2008212560-2008212552-DM4/可执行程序/knn.bat
2008212560-2008212552-DM4/可执行程序/myKNN.jar
2008212560-2008212552-DM4/源代码/core/Attribute.java
2008212560-2008212552-DM4/源代码/core/Instance.java
2008212560-2008212552-DM4/源代码/core/InstanceSet.java
2008212560-2008212552-DM4/源代码/core/KNNcore.java
2008212560-2008212552-DM4/源代码/core/Target_Simil_Node.java
2008212560-2008212552-DM4/源代码/evaluate/Evaluate.java
2008212560-2008212552-DM4/源代码/file/ArffFileReader.java
2008212560-2008212552-DM4/源代码/util/MainDriver.java
2008212560-2008212552-DM4/源代码/util/QuickSort.java
2008212560-2008212552-DM4/设计及说明文档.docx
2008212560-2008212552-DM4/可执行程序/dataset
2008212560-2008212552-DM4/源代码/core
2008212560-2008212552-DM4/源代码/evaluate
2008212560-2008212552-DM4/源代码/file
2008212560-2008212552-DM4/源代码/util
2008212560-2008212552-DM4/可执行程序
2008212560-2008212552-DM4/源代码
2008212560-2008212552-DM4
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