小编Ris*_*e47的帖子

我正在尝试在不使用 sklearn 库的情况下构建混淆矩阵。我无法正确形成混淆矩阵。这是我的代码：

def comp_confmat():
    currentDataClass = [1,3,3,2,5,5,3,2,1,4,3,2,1,1,2]    
    predictedClass = [1,2,3,4,2,3,3,2,1,2,3,1,5,1,1]
    cm = []
    classes = int(max(currentDataClass) - min(currentDataClass)) + 1 #find number of classes

    for c1 in range(1,classes+1):#for every true class
        counts = []
        for c2 in range(1,classes+1):#for every predicted class
            count = 0
            for p in range(len(currentDataClass)):
                if currentDataClass[p] == predictedClass[p]:
                    count += 1
            counts.append(count)
        cm.append(counts)
    print(np.reshape(cm,(classes,classes)))

然而这会返回：

[[7 7 7 7 7]
[7 7 7 7 7]
[7 7 7 7 7]
[7 7 7 7 7] …