机器学习之--归一特征值

#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.        ]]