python - 如果给定的数据在使用 R 或 Python 的范围（-1 到 1）内，如何以 (-3 ,-2,-1,0,1,2,3) 格式规范化数据？

Question

值：0.344 -0.124 0.880 0 0.910 -0.800

Answer 1

您可以尝试cut()在 R 中使用函数将值划分为区间。

value <- c(0.344, -0.124, 0.880, 0, 0.910, -0.800)
value.normalized <- cut(
  x = value, breaks = seq(-1, 1, length.out = 8), 
  labels = -3:3, include.lowest = TRUE, right = TRUE
)

(value.normalized)
1  0  3  0  3  -3
Levels: -3 -2 -1 0 1 2 3

Answer 2

您可以执行以下操作将任何数据标准化为给定比例：

>>> Data = [0.9, 0.2, 0.3, 0.4]
>>> lower, upper =-3, 3
>>> Data_norm = [lower + (upper - lower) * x for x in Data]
>>> Data_norm
[2.4000000000000004, -1.7999999999999998, -1.2000000000000002, -0.5999999999999996]

Answer 3

利用sklearn.preprocessing.minmax_scale

In [1]: from sklearn.preprocessing import minmax_scale


In [2]: value = [0.344,-0.124,0.880,0,0.910,-0.800]


In [3]: in_range = [-1, 1]


In [4]: value_scaled = minmax_scale(value + in_range, feature_range=(-3,3))


In [5]: value_scaled[:-2]

Out[5]: array([ 1.032, -0.372,  2.64 ,  0.   ,  2.73 , -2.4  ])