机器学习课程 matlab 练习
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-2.0184 -0.3825 0.6142 -9.1767
Columns 9837 through 9840
-8.3120 0.1415 -4.8130 -7.7481
Columns 9841 through 9844
-1.5691 -10.9133 -7.4672 -8.9653
Columns 9845 through 9848
-2.4616 0.1880 -3.6540 -1.2658
Columns 9849 through 9852
-1.0558 -3.7971 -7.6080 -3.1290
Columns 9853 through 9856
-4.9563 -9.5417 -7.7662 -1.2697
Columns 9857 through 9860
-9.6446 -4.9761 -8.4076 -4.2291
Columns 9861 through 9864
-9.1124 -9.9738 -5.2988 -8.8021
Columns 9865 through 9868
-1.8598 -4.3520 -7.0790 -7.0959
Columns 9869 through 9872
-12.3190 -6.0332 0.9059 -5.0268
Columns 9873 through 9876
-9.2393 -4.9415 -3.6955 -10.1832
Columns 9877 through 9880
-4.3342 -1.4838 -5.2785 -6.9504
Columns 9881 through 9884
-9.2075 -5.7782 -9.1968 -7.0501
Columns 9885 through 9888
-7.3171 -6.1496 -4.5279 -7.3322
Columns 9889 through 9892
-5.7798 -11.4195 -2.8303 -9.1350
Columns 9893 through 9896
-6.8877 -5.4628 -3.1701 -8.5331
Columns 9897 through 9900
-5.9152 -7.8587 -9.4375 -6.1149
Columns 9901 through 9904
-6.5394 -6.1288 -9.2587 -7.6269
Columns 9905 through 9908
-4.9465 -3.8037 -6.8552 0.2933
Columns 9909 through 9912
-9.2141 -10.2395 -0.8304 -8.9328
Columns 9913 through 9916
-6.5980 -9.1353 -9.7108 -8.4459
Columns 9917 through 9920
-6.5151 -7.4159 -3.2576 -7.3234
Columns 9921 through 9924
-1.9867 -8.6006 -10.9317 -5.0675
Columns 9925 through 9928
-1.8249 -6.7361 -2.0934 -6.7699
Columns 9929 through 9932
-8.0008 -9.9162 -2.6141 -10.0977
Columns 9933 through 9936
-7.0316 -8.4644 -8.4451 -6.8971
Columns 9937 through 9940
-5.5468 -5.2536 -8.6704 -4.9223
Columns 9941 through 9944
-4.3715 -6.4435 -6.7186 -9.8239
Columns 9945 through 9948
-5.0186 -0.7944 -3.6310 -6.3637
Columns 9949 through 9952
-4.1770 -5.4147 -4.1884 -5.6102
Columns 9953 through 9956
-5.9698 -0.9725 -5.6105 -3.9811
Columns 9957 through 9960
-3.5397 -1.8038 -6.4922 -4.0126
Columns 9961 through 9964
-5.7926 -7.5272 -6.3233 -4.0889
Columns 9965 through 9968
-8.3627 -0.9932 -0.0429 -8.3054
Columns 9969 through 9972
-7.0970 -4.5402 -4.7260 -1.6203
Columns 9973 through 9976
-6.2258 -0.9586 -8.6405 -5.7459
Columns 9977 through 9980
-4.9770 -9.0576 -5.8128 -6.8386
Columns 9981 through 9984
-3.2877 -4.2744 -0.1379 -2.8501
Columns 9985 through 9988
-5.6746 -12.0665 -6.4145 -8.4306
Columns 9989 through 9992
1.5577 -5.7557 -4.8122 -4.7491
Columns 9993 through 9996
-6.3558 -11.7839 0.6138 -4.8644
Columns 9997 through 10000
-8.5119 -6.7188 -0.9599 -5.5092
>> hist(w)
>> I = eye(3)
I =
1 0 0
0 1 0
0 0 1
>> I
I =
1 0 0
0 1 0
0 0 1
>> help help
help Display help text in Command Window.
help, by itself, lists all primary help topics. Each primary topic
corresponds to a folder name on the MATLAB search path.
help NAME displays the help for the functionality specified by NAME,
such as a function, operator symbol, method, class, or toolbox.
NAME can include a partial path.
Some classes require that you specify the package name. Events,
properties, and some methods require that you specify the class
name. Separate the components of the name with periods, using one
of the following forms:
help CLASSNAME.NAME
help PACKAGENAME.CLASSNAME
help PACKAGENAME.CLASSNAME.NAME
If NAME is the name of both a folder and a function, help displays
help for both the folder and the function. The help for a folder
is usually a list of the program files in that folder.
If NAME appears in multiple folders on the MATLAB path, help displays
information about the first instance of NAME found on the path.
NOTE:
In the help, some function names are capitalized to make them
stand out. In practice, type function names in lowercase. For
functions that are shown with mixed case (such as javaObject),
type the mixed case as shown.
EXAMPLES:
help close % help for the CLOSE function
help database/close % help for CLOSE in the Database Toolbox
help database % list of functions in the Database Toolbox
% and help for the DATABASE function
help containers.Map.isKey % help for isKey method
See also doc, docsearch, lookfor, matlabpath, which.
Reference page for help
Other functions named help
>> help docsearch
docsearch Help browser search.
docsearch opens the Help browser and displays the documentation home
page. If the Help browser is already open, but not visible, then
docsearch brings it to the foreground.
docsearch TEXT searches the documentation for pages with words that match
the specified expression. To search third-party or custom documentation,
you must first run the BUILDDOCSEARCHDB command to build a search database
for the additional help files.
Examples:
docsearch plot
docsearch plot tools
docsearch(\'plot tools\')
See also doc.
Reference page for docsearch
>> A
A =
1 2
3 4
5 6
>> size(A)
ans =
3 2
>> sz = size(A)
sz =
3 2
>> size(sz)
ans =
1 2
>> size(A, 1)
ans =
3
>> v = [1 2 3 4]
v =
1 2 3 4
>> length(v)
ans =
4
>> length(v)
ans =
4
>> pwd
ans =
D:\Software\Matlab\bin
>> cd
D:\Software\Matlab\bin
>> cd C:\User\
Error using cd
Cannot CD to C:\User\ (Name is nonexistent or
not a directory).
>> load
Error using load
Unable to read file \'matlab.mat\'. No such file
or directory.
>> who
Your variables are:
A I ans sz w
C a c v
>> cd C:\Users\BruceDu\Desktop\
>> load("test.dat")
load("test.dat")
↑
Error: The input character is not valid in
MATLAB statements or expressions.
>> load(\'test.dat\')
>> who
Your variables are:
A I ans sz v
C a c test w
>> test
test =
134 33
32 44
43 5
22 6
67 8
>> size(test)
ans =
5 2
>> who
Your variables are:
A I ans sz v
C a c test w
>> whos
Name Size Bytes Class Attributes
A 3x2 48 double
C 2x3 48 double
I 3x3 72 double
a 1x1 8 double
ans 1x2 16 double
c 1x1 1 logical
sz 1x2 16 double
test 5x2 80 double
v 1x4 32 double
w 1x10000 80000 double
>> clear test
>> whos
Name Size Bytes Class Attributes
A 3x2 48 double
C 2x3 48 double
I 3x3 72 double
a 1x1 8 double
ans 1x2 16 double
c 1x1 1 logical
sz 1x2 16 double
v 1x4 32 double
w 1x10000 80000 double
>> load(\'test.dat\')
>> whos
Name Size Bytes Class Attributes
A 3x2 48 double
C 2x3 48 double
I 3x3 72 double
a 1x1 8 double
ans 1x2 16 double
c 1x1 1 logical
sz 1x2 16 double
test 5x2 80 double
v 1x4 32 double
w 1x10000 80000 double
>> top_test = test(1:2)
top_test =
134 32
>> test
test =
134 33
32 44
43 5
22 6
67 8
>> save hello.mat top_test
>> save hello.txt top_test
>> A(3,2)
ans =
6
>> A
A =
1 2
3 4
5 6
>> A(2,:)
ans =
3 4
>> A(:, 2)
ans =
2
4
6
>> A([1,3], :)
ans =
1 2
5 6
>> A(:, 2) = [10; 12, 14]
Dimensions of matrices being concatenated are
not consistent.
>> A(:, 2) = [10, 12, 14]
A =
1 10
3 12
5 14
>> A = [A, [100, 120, 140]]
Error using horzcat
Dimensions of matrices being concatenated are
not consistent.
>> A = [A, [100; 120; 140]]
A =
1 10 100
3 12 120
5 14 140
>> A(:)
ans =
1
3
5
10
12
14
100
120
140
>> A = [1 2; 3 4; 5 6]
A =
1 2
3 4
5 6
>> B = [11 12; 13 14; 15 16]
B =
11 12
13 14
15 16
>> C = [A B]
C =
1 2 11 12
3 4 13 14
5 6 15 16
>> C = [A; B]
C =
1 2
3 4
5 6
11 12
13 14
15 16
>> size(C)
ans =
6 2
>> C = [A, B]
C =
1 2 11 12
3 4 13 14
5 6 15 16
>> A
A =
1 2
3 4
5 6
>> B = [11 12; 13 14; 15 16]
B =
11 12
13 14
15 16
>> C = [ 1 1; 2 2]
C =
1 1
2 2
>> A .* B
ans =
11 24
39 56
75 96
>> A .^ 2
ans =
1 4
9 16
25 36
>> v = [1; 2; 3]
v =
1
2
3
>> 1 ./ v
ans =
1.0000
0.5000
0.3333
>> log(v)
ans =
0
0.6931
1.0986
>> exp(v)
ans =
2.7183
7.3891
20.0855
>> abs(v)
ans =
1
2
3
>> abs([-1; 2; -3])
ans =
1
2
3
>> v + ones(length(v), 1)
ans =
2
3
4
>> A\'
ans =
1 3 5
2 4 6
>> A
A =
1 2
3 4
5 6
>> (A\')\'
ans =
1 2
3 4
5 6
>> val = max(a)
val =
3.1416
>> a
a =
3.1416
>> a < 3
ans =
0
>> A < 2
ans =
1 0
0 0
0 0
>> find(A < 2)
ans =
1
>> A = magic(3)
A =
8 1 6
3 5 7
4 9 2
>> help magic
magic Magic square.
magic(N) is an N-by-N matrix constructed from the integers
1 through N^2 with equal row, column, and diagonal sums.
Produces valid magic squares for all N > 0 except N = 2.
Reference page for magic
>> help find
find Find indices of nonzero elements.
I = find(X) returns the linear indices corresponding to
the nonzero entries of the array X. X may be a logical expression.
Use IND2SUB(SIZE(X),I) to calculate multiple subscripts from
the linear indices I.
I = find(X,K) returns at most the first K indices corresponding to
the nonzero entries of the array X. K must be a positive integer,
but can be of any numeric type.
I = find(X,K,\'first\') is the same as I = find(X,K).
I = find(X,K,\'last\') returns at most the last K indices corresponding
to the nonzero entries of the array X.
[I,J] = find(X,...) returns the row and column indices instead of
linear indices into X. This syntax is especially useful when working
with sparse matrices. If X is an N-dimensional array where N > 2, then
J is a linear index over the N-1 trailing dimensions of X.
[I,J,V] = find(X,...) also returns a vector V containing the values
that correspond to the row and column indices I and J.
Example:
A = magic(3)
find(A > 5)
finds the linear indices of the 4 entries of the matrix A that are
greater than 5.
[rows,cols,vals] = find(speye(5))
finds the row and column indices and nonzero values of the 5-by-5
sparse identity matrix.
See also sparse, ind2sub, relop, nonzeros.
Reference page for find
Other functions named find
>> sum(a)
ans =
3.1416
>> prod(a)
ans =
3.1416
>> ceil(0.5)
ans =
1
>> floor(0.5)
ans =
0
>> rand(3)
ans =
0.5437 0.2492 0.5598
0.4425 0.2851 0.4151
0.1837 0.5295 0.9057
>> max(rand(3),rand(3))
ans =
0.3051 0.2553 0.8383
0.6498 0.3582 0.5901
0.9801 0.8059 0.4685
>> max(A,[], 1)
ans =
8 9 7
>> A = magic(9)
A =
Columns 1 through 8
47 58 69 80 1 12 23 34
57 68 79 9 11 22 33 44
67 78 8 10 21 32 43 54
77 7 18 20 31 42 53 55
6 17 19 30 41 52 63 65
16 27 29 40 51 62 64 75
26 28 39 50 61 72 74 4
36 38 49 60 71 73 3 14
37 48 59 70 81 2 13 24
Column 9
45
46
56
66
76
5
15
25
35
>> sum(A,1)
ans =
Columns 1 through 8
369 369 369 369 369 369 369 369
Column 9
369
>> A .*eye(9)
Error: "A" was previously used as a variable,
conflicting with its use here as the name of a
function or command.
See "How MATLAB Recognizes Command Syntax" in
the MATLAB documentation for details.
>> A .* eye(9)
ans =
Columns 1 through 8
47 0 0 0 0 0 0 0
0 68 0 0 0 0 0 0
0 0 8 0 0 0 0 0
0 0 0 20 0 0 0 0
0 0 0 0 41 0 0 0
0 0 0 0 0 62 0 0
0 0 0 0 0 0 74 0
0 0 0 0 0 0 0 14
0 0 0 0 0 0 0 0
Column 9
0
0
0
0
0
0
0
0
35
>> sum(A .* eye(9))
ans =
Columns 1 through 8
47 68 8 20 41 62 74 14
Column 9
35
>> sum(sum(A .* eye(9)))
ans =
369
>> pinv(A)
ans =
Columns 1 through 4
0.0005 -0.0012 0.0017 0.0126
0.0003 0.0003 0.0128 -0.0122
-0.0011 0.0140 -0.0120 0.0003
0.0126 -0.0120 0.0003 0.0003
-0.0108 0.0003 0.0003 0.0003
0.0003 0.0005 0.0001 -0.0011
0.0003 0.0003 0.0003 0.0005
0.0003 0.0003 -0.0011 0.0017
0.0003 0.0003 0.0003 0.0003
Columns 5 through 8
-0.0121 0.0003 0.0003 0.0003
0.0003 -0.0011 0.0017 0.0003
0.0005 0.0001 0.0003 0.0003
-0.0011 0.0017 0.0005 0.0001
0.0003 0.0003 0.0003 0.0003
0.0017 0.0003 0.0003 0.0126
0.0001 0.0003 0.0126 -0.0134
0.0003 0.0128 -0.0122 0.0003
0.0127 -0.0120 -0.0011 0.0018
Column 9
0.0003
0.0003
0.0003
0.0003
0.0114
-0.0120
0.0017
0.0003
0.0001
>> t = [0: 0.01:0.98];
>> y1 = sin(2 * pi * 4 * t)
y1 =
Columns 1 through 4
0 0.2487 0.4818 0.6845
Columns 5 through 8
0.8443 0.9511 0.9980 0.9823
Columns 9 through 12
0.9048 0.7705 0.5878 0.3681
Columns 13 through 16
0.1253 -0.1253 -0.3681 -0.5878
Columns 17 through 20
-0.7705 -0.9048 -0.9823 -0.9980
Columns 21 through 24
-0.9511 -0.8443 -0.6845 -0.4818
Columns 25 through 28
-0.2487 -0.0000 0.2487 0.4818
Columns 29 through 32
0.6845 0.8443 0.9511 0.9980
Columns 33 through 36
0.9823 0.9048 0.7705 0.5878
Columns 37 through 40
0.3681 0.1253 -0.1253 -0.3681
Columns 41 through 44
-0.5878 -0.7705 -0.9048 -0.9823
Columns 45 through 48
-0.9980 -0.9511 -0.8443 -0.6845
Columns 49 through 52
-0.4818 -0.2487 -0.0000 0.2487
Columns 53 through 56
0.4818 0.6845 0.8443 0.9511
Columns 57 through 60
0.9980 0.9823 0.9048 0.7705
Columns 61 through 64
0.5878 0.3681 0.1253 -0.1253
Columns 65 through 68
-0.3681 -0.5878 -0.7705 -0.9048
Columns 69 through 72
-0.9823 -0.9980 -0.9511 -0.8443
Columns 73 through 76
-0.6845 -0.4818 -0.2487 -0.0000
Columns 77 through 80
0.2487 0.4818 0.6845 0.8443
Columns 81 through 84
0.9511 0.9980 0.9823 0.9048
Columns 85 through 88
0.7705 0.5878 0.3681 0.1253
Columns 89 through 92
-0.1253 -0.3681 -0.5878 -0.7705
Columns 93 through 96
-0.9048 -0.9823 -0.9980 -0.9511
Columns 97 through 99
-0.8443 -0.6845 -0.4818
>> plot(t,y1)
>> y2 = cos(2 * pi * 4 * t)
y2 =
Columns 1 through 4
1.0000 0.9686 0.8763 0.7290
Columns 5 through 8
0.5358 0.3090 0.0628 -0.1874
Columns 9 through 12
-0.4258 -0.6374 -0.8090 -0.9298
Columns 13 through 16
-0.9921 -0.9921 -0.9298 -0.8090
Columns 17 through 20
-0.6374 -0.4258 -0.1874 0.0628
Columns 21 through 24
0.3090 0.5358 0.7290 0.8763
Columns 25 through 28
0.9686 1.0000 0.9686 0.8763
Columns 29 through 32
0.7290 0.5358 0.3090 0.0628
Columns 33 through 36
-0.1874 -0.4258 -0.6374 -0.8090
Columns 37 through 40
-0.9298 -0.9921 -0.9921 -0.9298
Columns 41 through 44
-0.8090 -0.6374 -0.4258 -0.1874
Columns 45 through 48
0.0628 0.3090 0.5358 0.7290
Columns 49 through 52
0.8763 0.9686 1.0000 0.9686
Columns 53 through 56
0.8763 0.7290 0.5358 0.3090
Columns 57 through 60
0.0628 -0.1874 -0.4258 -0.6374
Columns 61 through 64
-0.8090 -0.9298 -0.9921 -0.9921
Columns 65 through 68
-0.9298 -0.8090 -0.6374 -0.4258
Columns 69 through 72
-0.1874 0.0628 0.3090 0.5358
Columns 73 through 76
0.7290 0.8763 0.9686 1.0000
Columns 77 through 80
0.9686 0.8763 0.7290 0.5358
Columns 81 through 84
0.3090 0.0628 -0.1874 -0.4258
Columns 85 through 88
-0.6374 -0.8090 -0.9298 -0.9921
Columns 89 through 92
-0.9921 -0.9298 -0.8090 -0.6374
Columns 93 through 96
-0.4258 -0.1874 0.0628 0.3090
Columns 97 through 99
0.5358 0.7290 0.8763
>> plot(t, y2)
>> plot(t,y1)
>> hold on;
>> plot(t, y2)
>> xlabel(\'time\')
>> ylabel(\'value\')
>> legend(\'sin\', \'cos\')
>> title(\'my plot\')
>> pwd
ans =
C:\Users\BruceDu\Desktop
>> print -dpng \'myplot.png\'
>> figure(1); plot(t, y1);
>> close
>> figure(1); plot(t, y1);
>> figure(2); plot(t, y2);
>> subplot(1, 2, 1);
>> plot(t, y1)
>> subplot(1,2,2)
>> plot(t, y2)
>> axis([0.5, 1 -1, 1])
>> A = magic(5)
A =
17 24 1 8 15
23 5 7 14 16
4 6 13 20 22
10 12 19 21 3
11 18 25 2 9
>> imagesc(A)
>> clf
>> imagsc(A)
Undefined function or variable \'imagsc\'.
Did you mean:
>> imagesc(A)
>> imagesc(A), colorbar, colorbar gray
Error using colorbar (line 171)
Unrecognized input or invalid parameter/value
pair arguments.
>> imagesc(A), colorbar, colormap gray
>> for i = 1:10,
>> indices = 1:10
indices =
Columns 1 through 8
1 2 3 4 5 6 7 8
Columns 9 through 10
9 10
>> for i = indices,
disp(i)
end;
1
2
3
4
5
6
7
8
9
10
>> i =1;
>> while i <= 5;
v(i) = 100;
i = i + 1;
end;
>> v
v =
100
100
100
100
100
>> while true,
v(i) = 9999;
i = i +1
if i == 100,
break;
end;
end;
i =
7
i =
8
i =
9
i =
10
i =
11
i =
12
i =
13
i =
14
i =
15
i =
16
i =
17
i =
18
i =
19
i =
20
i =
21
i =
22
i =
23
i =
24
i =
25
i =
26
i =
27
i =
28
i =
29
i =
30
i =
31
i =
32
i =
33
i =
34
i =
35
i =
36
i =
37
i =
38
i =
39
i =
40
i =
41
i =
42
i =
43
i =
44
i =
45
i =
46
i =
47
i =
48
i =
49
i =
50
i =
51
i =
52
i =
53
i =
54
i =
55
i =
56
i =
57
i =
58
i =
59
i =
60
i =
61
i =
62
i =
63
i =
64
i =
65
i =
66
i =
67
i =
68
i =
69
i =
70
i =
71
i =
72
i =
73
i =
74
i =
75
i =
76
i =
77
i =
78
i =
79
i =
80
i =
81
i =
82
i =
83
i =
84
i =
85
i =
86
i =
87
i =
88
i =
89
i =
90
i =
91
i =
92
i =
93
i =
94
i =
95
i =
96
i =
97
i =
98
i =
99
i =
100
>> i
i =
100
>> squareThisNumber(3)
Undefined function or variable
\'squareThisNumber\'.
>> squareThisNumber(3)
Undefined function or variable
\'squareThisNumber\'.
Did you mean:
>> squraThisNumber(3)
y =
9
ans =
9
>> [a, b] = squareAndCubeThisNumber(3)
y1 =
9
y2 =
27
a =
9
b =
27
>> X = [1 1; 1 2; 1 3]
X =
1 1
1 2
1 3
>> y = [1; 2; 3]
y =
1
2
3
>> theta = [0;1];
>> costFunction(X, y, theta)
sqrErrors =
0
0
0
ans =
0
>> theta = [0; 0]
theta =
0
0
>> costFunction(X, y, theta)
sqrErrors =
1
4
9
ans =
2.3333
>>
定义的三个函数
- squraThisNumber.m
function [ y ] = squraThisNumber( x )
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
y = x ^ 2
end
- squareAndCubeThisNumber.m
function [ y1, y2 ] = squareAndCubeThisNumber( x )
%UNTITLED2 Summary of this function goes here
% Detailed explanation goes here
y1 = x ^ 2
y2 = x ^ 3
end
- costFunction.m
function [ J ] = costFunction( X, y, theta )
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
m = size(X, 1);
predictions = X * theta;
sqrErrors = (predictions - y) .^ 2
J = 1/(2 * m) * sum(sqrErrors);
end