Machine Learning-Overview of common matlab programming commands (NG-ml-class octave/MATLAB tutorial)

Source: Internet
Author: User

Machine Learning-Overview of common matlab programming commands

-- Summary from ng-ml-class octave/MATLAB tutorial Coursera

A. basic operations and moving data around1 in command line mode, you can use Shift + press enter to append the next line to output 2 length command to apply to the matrix, and return a higher one-dimensional dimension3 help + command is the display command. mat File Save hello. mat B uses binary compression to save the data. Save hello.txt V-ASCII is saved as a readable file. That is, the text format is 6: means every elements in this col7 A ([1 3], obtain data of all columns in rows 1st and 3. 8 A = [A, [100; 101; 102] Add a column Col vector [100,101,102] 9 size (a) After matrix) returns a matrix of 1 rows and 2 columns, indicating that the size of 1st and 2nd dimenxes is 10 C = [a B] equivalent to C = [a, B, concatenate the two matrices [] into the Concat Connection Matrix or the string 11 c = [A; B]; number indicates to add to the following row, so the corresponding number of rows is increased, the number of columns remains unchanged. B. computing on data12. * B is matrix/vector point multiplication a * B is matrix multiplication 13 log (V) and exp (v) Evaluate the logarithm and exponent 14 ABS () Based on E () returns the value and index of the maximum element in the matrix. [Val, IND] = max () 17 A <3 determines whether each of the values of a is less than 3. If the value is less than 3, true is returned for the corresponding position. Otherwise, false18 find (A <3) is returned for the position) returns the index 19 magic square with all values less than 3 in the matrix.

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 records t n = 2.20 [R, C] = find (A> = 7) returns the row of an element greater than or equal to 7 and the index of Col 21. Prod (a) calculates the product of all elements in matrix A. Floor () round-down integer Ceil (a) For elements in matrix A round-up integer rand (3) to generate a random matrix max (A, [], 1) of 3x3) evaluate the maximum value of each column of matrix A (1 indicates Dimension 1) max (A, [], 2) for each row of matrix A sum (, 1) sum the first dimension (that is, each column) of matrix A (note that the first dimension in MATLAB is a column by default, followed by a row, and so on ...) Sum (A, 2) Sums sum (. * eye (9) is used to calculate the sum of diagonal elements of matrix A. 22. flipud flip matrix in up/down direction. flip the matrix up and down, similar to fliplr, rot90, flipdim.
Flipud (x) returns X with columns preserved and rows flipped
In the up/down direction. For example,
X = 1 4 becomes 3 6
2 5 2 5
3 6 1 423 pinv (A) and inv (a) Calculate the inverse matrices C and plo1_data24 t of matrix A = [0.1: 0.01: 0.98] Y = sin (t) plot (T, Y) Draw a sine curve 25 hold on; retain the current curve, draw a curve 26 x label calibration X axis description 27 legend ('sin', 'cos ') add legend 28 title ('My plot') Add picture title 29 print-dpng 'myplot.png 'Save picture 30 line color annotation control B blue. point-Solid
G green o circle: dotted
R red X-mark-. dashdot
C cyan + plus -- dashed
M magenta * Star (none) No line
Y yellow S Square
K black D Diamond
W white V triangle (down)
^ Triangle (up)
<Triangle (left)
> Triangle (right)
P pentagram
H hexagram31 subplot to draw a subgraph. Multiple graphs are merged into one graph> subplot (, 1) % divides plot a 1X2 grid, access the 1st Element
> Plot (T, Y1)
> Subplot (1, 2)
> Plot (T, Y2) 32 grid plus grid 33 figure (1)

> Plot (T, Y1)
> Figure (2)
> Plot (T, Y2) draws the curves of Y1 and Y2 to 34 axis ([0.5 1-1]) in the two files named Figure1 and figure2. set the X axis to 0.5 ~ 1. the Y axis ranges from-1 ~ 135 CLF clear current figure.36 imagesc (a) imagesc Scale Data and display as image. draws matrix A into a small color square 37 imagesc (A), colorbar, colormap gray; colorbar displays the color gradient bar, color Description colormap sets colormap properties, that is, RGB three-color a color map matrix may have any number of rows, but it must have
Exactly 3 columns. Each row is interpreted as a color, with
First element specifying the intensity of red light, the second
Green, and the third blue. Color intensity can be specified on
Interval 0.0 to 1.0.38 A = 1; B = 2; C = 3; the values a = 1, B = 2, and a B C are not displayed, C = 3 will output the values D, control statements: For, while, if statements39 for loop for I =,
V (I) = 2 ^ I;
End;
> V

V =

2
4
8
16
32
64
128
256
512
1024> indices =
For I = indices,
Disp (I)
End; 40 while loop> while I <= 5,
V (I) = 100;
I = I + 1;
End;
> V

V =

100
100
100
100
100
64
128
256
512
1024

> I = 1;
> While true,
V (I) = 999;
I = I + 1;
If I = 6,
Break;
End;
End;
> Exit

V =

999
999
999
999
999
64
128
256
512
102441 if elseif judge branch statement V (1) = 2

V =

2
999
999
999
999
64
128
256
512
1024

> If V (1) = 1,
Disp ('the value is one ');
Elseif V (1) = 2,
Disp ('the value is two ');
Else
Disp ('the value is not one or two .');
End;
The value is the definition of the two42 function and the use of the definition function squarethisnumber. M file Function Y = squarethisnumber (x) y = x ^ 2; call squarethisnumber (5)

Ans =

25

43 addpath adds the path of the MATLAB search function 44 the function defined in MATLAB can return more than one value, which is different from C ++ and other programming languages, the function in C \ c ++ has a unique return value that allows multiple return values to facilitate programming. function [a, B] = squareandcubethisnumber (x) A = x ^ 2; B = x ^ 3; call> [x1, x2] = squareandcubethisnumber (5)

X1 =

25

X2 =

125

45 Cost Function J function example Function J = costfunctionj (X, Y, theta) % x is the "design matrix" containing our training examples. % Y is the class labels M = size (x, 1); % Number of training examplespredictions = x * Theta; % predictions of hypothesis on all M examplessqrerrors = (predictions-Y ). ^ 2; % squared errorsj = 1/(2 * m) * sum (sqrerrors );
Call X = [1 1; 1 2; 1 3]; y = [1; 2; 3];

Theta = [0; 1];

> J = costfunctionj (X, Y, theta)

J =

0

% Squared errors is 0 in this example> Theta = [0; 0]

Theta =

0
0

> J = costfunctionj (X, Y, theta)

J =

2.3333

% Squared errors is 2.3333 in this example % which is (1 ^ 2 + 2 ^ 2 + 3 ^ 2)/(2*3) = 2.3333
E. vectorizationthe implementation algorithm of "vectorizationmatlab" can reduce unnecessary loops and calculate the values of all vectors in the same way. This is a faster and more efficient algorithm implementation idea, be aware of the differences between the algorithm and other programming languages Java, C, and C ++ in the "vectorized" and "matrix" operation variables in MATLAB.

Contact Us

The content source of this page is from Internet, which doesn't represent Alibaba Cloud's opinion; products and services mentioned on that page don't have any relationship with Alibaba Cloud. If the content of the page makes you feel confusing, please write us an email, we will handle the problem within 5 days after receiving your email.

If you find any instances of plagiarism from the community, please send an email to: info-contact@alibabacloud.com and provide relevant evidence. A staff member will contact you within 5 working days.

A Free Trial That Lets You Build Big!

Start building with 50+ products and up to 12 months usage for Elastic Compute Service

  • Sales Support

    1 on 1 presale consultation

  • After-Sales Support

    24/7 Technical Support 6 Free Tickets per Quarter Faster Response

  • Alibaba Cloud offers highly flexible support services tailored to meet your exact needs.