In [4]:

    

import numpy as np
from sklearn.datasets import fetch_mldata
data = fetch_mldata('leukemia')
print(data)


    

    




{'data': array([[-1.46236 , -0.645135, -0.835925, ..., -0.596842, -0.471106,
        -0.959575],
       [-0.664799,  0.206146, -0.368575, ..., -0.865241, -0.664888,
        -0.543433],
       [-0.200487,  0.379941, -2.38278 , ..., -0.496304, -0.433475,
        -0.896774],
       ..., 
       [ 1.09604 ,  1.64385 ,  0.681936, ...,  0.973412, -0.264428,  1.8375  ],
       [ 0.50366 ,  0.426793,  0.294282, ...,  0.036783, -0.541209,
         0.358362],
       [-0.455835, -0.071517, -0.526423, ..., -0.110748, -0.339931,
        -0.068667]]), 'COL_NAMES': ['label', 'data'], 'DESCR': 'mldata.org dataset: leukemia', 'target': array([ 1,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1,
        1,  1,  1,  1,  1,  1,  1,  1,  1,  1, -1, -1, -1, -1, -1, -1, -1,
       -1, -1, -1, -1,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1, -1, -1,
       -1, -1, -1,  1,  1, -1, -1,  1, -1, -1, -1, -1, -1, -1, -1,  1,  1,
        1,  1,  1,  1])}

In [2]:

    

quickref


    

In [3]:

    

import sklearn
print(sklearn.__version__)


    

    




0.18.2

In [ ]: