#归一化数值 防止特征值权值过大 方法：newdata = (olddata - min)/(max - min) a = np.array([[1,0.1,7],[1.5,0.1,2],[1.6,0.4,3],[1.2,0.4,4],[1.3,0.5,12]]) # a # [[ 1. 0.1 7. ] # [ 1.5 0.1 2. ] # [ 1.6 0.4 3. ] # [ 1.2 0.4 4. ] # [ 1.3 0.5 12. ]] Max = a.max(0) Min = a.min(0) # Max:[ 1.6 0.5 12. ],Min:[1. 0.1 2. ] cha1 = a - Min # cha1 # [[ 0. 0. 5. ] # [ 0.5 0. 0. ] # [ 0.6 0.3 1. ] # [ 0.2 0.3 2. ] # [ 0.3 0.4 10. ]] ranges = Max - Min result = cha1 / ranges # result # [[0. 0. 0.5 ] # [0.83333333 0. 0. ] # [1. 0.75 0.1 ] # [0.33333333 0.75 0.2 ] # [0.5 1. 1. ]]