Machine learn in Python chapter II 2.1.1

1 approx sklearn.datasets

from sklearn.datasets import Load_iris

Import NumPy as NP

data = Load_iris ()

The properties of data are as follows:

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The data is stored in the. Data key

The type of each observation object is stored in the. Target property of the dataset.

>>>print (target)
[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 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 2 2 2 2 2 2 2 2 2 2 2
2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
2 2]

The type of characteristics of the data is stored in the. Feature_names property of the DataSet.

>>>print (data[' target_names ')
[' Setosa ' versicolor ' virginica ']

2 About traversal problems

A: Traversing the ordinal of an item I

For item in sequence:

Process (item)

B:

For index, item in enumerate (sequence):

Process (index, item)

3:subplot (M,n,i)

For example, subplot (2,3,2), which divides the entire plane into 2 rows and 3 columns, is now the 2nd position in the left-to-right order of the drawing

4 zip in Python

Zip return list

X=[1, 2, 3, 4, 5]y=[6, 7, 8, 9, 10]zip (x, y) got [(1, 6), (2, 7), (3, 8), (4, 9), (5, 10)]

5 range () function

Range ([Start,] stop [, step])
# start selectable number of parameters, start
#stop the number of terminations. Assuming that range has only one parameter x, it produces a list of integers that include 0 to X-1
#step Optional parameters, step size
6 annoying whitespace problem error: indentationerror:expected an indented block

For I in range (1,5): space carriage return

Space print (i) Enter

Else: space carriage return

space print (" ") Enter carriage return

>>> for I in range (1,5):
... print (i)
.. else:
... print ("dead!")
...
1
2
3
4
dead!

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Machine learn in Python chapter II 2.1.1