Read data file in the form:
x11 [TAB] x12 [TAB] ... x1n [TAB] y1
x21 [TAB] x22 [TAB] ... x2n [TAB] y2
. . . . .
. . . . .
. . . . .
xm1 [TAB] xm2 [TAB] ... xmn [TAB] ym
where xij are float and yi are integer.
Input
- file - data file name
Output
- x - data [2D numpy array float]
- y - classes [1D numpy array integer]
Example:
>>> from numpy import *
>>> from mlpy import *
>>> x, y = data_fromfile('data_example.dat')
>>> x
array([[ 1.1, 2. , 5.3, 3.1],
... [ 3.7, 1.4, 2.3, 4.5],
... [ 1.4, 5.4, 3.1, 1.4]])
>>> y
array([ 1, -1, 1])
Read data file in the form:
x11 [TAB] x12 [TAB] ... x1n [TAB]
x21 [TAB] x22 [TAB] ... x2n [TAB]
. . . .
. . . .
. . . .
xm1 [TAB] xm2 [TAB] ... xmn [TAB]
where xij are float.
Input
- file - data file name
Output
- x - data [2D numpy array float]
Example:
>>> from numpy import *
>>> from mlpy import *
>>> x, y = data_fromfile('data_example.dat')
>>> x
array([[ 1.1, 2. , 5.3, 3.1],
... [ 3.7, 1.4, 2.3, 4.5],
... [ 1.4, 5.4, 3.1, 1.4]])
Write data file in the form:
x11 [sep] x12 [sep] ... x1n [sep] y1
x21 [sep] x22 [sep] ... x2n [sep] y2
. . . . .
. . . . .
. . . . .
xm1 [sep] xm2 [sep] ... xmn [sep] ym
where xij are float and yi are integer.
Input
- file - data file name
- x - data [2D numpy array float]
- y - classes [1D numpy array integer]
- sep - separator
Write data file in the form:
x11 [sep] x12 [sep] ... x1n [sep]
x21 [sep] x22 [sep] ... x2n [sep]
. . . .
. . . .
. . . .
xm1 [sep] xm2 [sep] ... xmn [sep]
where xij are float.
Input
- file - data file name
- x - data [2D numpy array float]
- sep - separator
Normalize numpy array (2D) x.
Input
- x - data [2D numpy array float]
Output
- normalized data
Example:
>>> from numpy import *
>>> from mlpy import *
>>> x = array([[ 1.1, 2. , 5.3, 3.1],
... [ 3.7, 1.4, 2.3, 4.5],
... [ 1.4, 5.4, 3.1, 1.4]])
>>> data_normalize(x)
array([[-0.9797065 , -0.48295391, 1.33847226, 0.12418815],
... [ 0.52197912, -1.13395464, -0.48598056, 1.09795608],
... [-0.75217354, 1.35919078, 0.1451563 , -0.75217354]])
Standardize numpy array (2D) x and optionally standardize p using mean and std of x.
Input
- x - data [2D numpy array float]
- p - optional data [2D numpy array float]
Output
- standardized data
Example:
>>> from numpy import *
>>> from mlpy import *
>>> x = array([[ 1.1, 2. , 5.3, 3.1],
... [ 3.7, 1.4, 2.3, 4.5],
... [ 1.4, 5.4, 3.1, 1.4]])
>>> data_standardize(x)
array([[-0.67958381, -0.43266792, 1.1157668 , 0.06441566],
... [ 1.1482623 , -0.71081158, -0.81536804, 0.96623494],
... [-0.46867849, 1.1434795 , -0.30039875, -1.0306506 ]])