function?[pclass_cnt]=KNN（train_datatrain_labeltest_datanum_classK）

%使用KNN算法預測結果
m=size（train_data1）;%number?of?samples
n=size（train_data2）;%number?of?features
m1=size（test_data1）;%number?of?test?samples

%計算測試數據與訓練數據的歐氏距離
distance=zeros（m1m）;
for?i=1:m1
????for?j=1:m
????????for?l=1:n
????????????distance（ij）=（test_data（il）-train_data（jl））^2+distance（ij）;
????????end
????end
????fprintf（‘\nFinished?computing?the?%dth?test?sample?distance\n‘i）;
end
distance=sqrt（distance）;


%找出每行最小的K個點


[~index]=sort（distance2）;

class_cnt=zeros（m1num_class）;
for?l=1:m1
for?i=1:num_class
????for?j=1:K
????????if（train_label（index（lj））==mod（inum_class））
????????????class_cnt（li）=class_cnt（li）+1;
????????end
????end
end
end
fprintf（‘\nfinished?computing?the?class_cnt?matrix?which?shows?the?number?of?different?classes?in?the?neighbor\n‘）;
[~p]?=?max（?class_cnt[]2）;?%?求矩陣（X*all_theta‘）每行的最大值，p?記錄矩陣每行的最大值的索引
p=mod（pnum_class）;

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2017-11-14?23:37??KNN\
?????文件?????4238592??2017-11-13?20:59??KNN\CIFAR-features.mat
?????文件????????1045??2017-11-12?20:18??KNN\KNN.m
?????文件?????????854??2017-11-10?16:27??KNN\loadMNISTImages.m
?????文件?????????533??2017-11-08?10:23??KNN\loadMNISTLabels.m
?????文件?????7840016??1998-01-26?23:07??KNN\t10k-images.idx3-ubyte
?????文件???????10008??1998-01-26?23:07??KNN\t10k-labels.idx1-ubyte
?????文件?????????333??2017-11-14?23:37??KNN\test_KNN_CIFAR.m
?????文件?????????515??2017-11-14?23:37??KNN\test_KNN_MNIST.m
?????文件????47040016??1996-11-18?23:36??KNN\train-images.idx3-ubyte
?????文件???????60008??1996-11-18?23:36??KNN\train-labels.idx1-ubyte