Description: 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
File list (Check if you may need any files):
2008212560-2008212552-DM4
.........................\readme.txt
.........................\可执行程序
.........................\..........\dataset
.........................\..........\.......\soybean-large-test.arff
.........................\..........\.......\soybean-large-train.arff
.........................\..........\knn.bat
.........................\..........\myKNN.jar
.........................\源代码
.........................\......\core
.........................\......\....\Attribute.java
.........................\......\....\Instance.java
.........................\......\....\InstanceSet.java
.........................\......\....\KNNcore.java
.........................\......\....\Target_Simil_Node.java
.........................\......\evaluate
.........................\......\........\Evaluate.java
.........................\......\file
.........................\......\....\ArffFileReader.java
.........................\......\util
.........................\......\....\MainDriver.java
.........................\......\....\QuickSort.java
.........................\设计及说明文档.docx
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