nction plotDecisionBoundary (theta, X, y) LOTDECISIONBOUNDARY Plots the data points X and y into a new figure wi he decision boundary defined by theta PLOTDECISIONBOUNDARY (theta, X,y) plots the data points with + for the positive examples and o for the negative examples. X is assumed to be a either 1) Mx3 matrix, where the first column is an all-ones column for the intercept. 2) MxN, N>3 matrix, where the first column is all-ones Plot Data ptData (X (:,2:3), y); ld on size (X, 2) <= 3 % Only need 2 points to define a line, so choose two endpoints plot_x = [min (X (:, 2))-2, * Calculate the decision boundary line plot_y = (-1./theta (3)).* (theta (2).*plot_x + theta (1)); * Plot, and adjust axes for better viewing plot (plot_x, plot_y) * Legend, specific for the exercise legend ('Admitted', 'Not admitted', 'Decision Boundary') se axis ([30, 100, 30, 100]) * Here is the grid range u = linspace (-1, 1.5, 50); max (X (:, 2))+2]; olo olo olo olo olo olo olo olo olo olo olo olo
nction plotDecisionBoundary (theta, X, y) LOTDECISIONBOUNDARY Plots the data points X and y into a new figure wi he decision boundary defined by theta PLOTDECISIONBOUNDARY (theta, X,y) plots the data points with + for the positive examples and o for the negative examples. X is assumed to be a either 1) Mx3 matrix, where the first column is an all-ones column for the intercept. 2) MxN, N>3 matrix, where the first column is all-ones Plot Data ptData (X (:,2:3), y); ld on size (X, 2) <= 3 % Only need 2 points to define a line, so choose two endpoints plot_x = [min (X (:, 2))-2, * Calculate the decision boundary line plot_y = (-1./theta (3)).* (theta (2).*plot_x + theta (1)); * Plot, and adjust axes for better viewing plot (plot_x, plot_y) * Legend, specific for the exercise legend ('Admitted', 'Not admitted', 'Decision Boundary') se axis ([30, 100, 30, 100]) * Here is the grid range u = linspace (-1, 1.5, 50); max (X (:, 2))+2]; olo olo olo olo olo olo olo olo olo olo olo olo
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
Related questions
Question
![linspace (-1, 1.5, 50);
= zeros (length (u), length (v) ) ;
% Evaluate z = theta*x over the grid
for i = 1:length (u)
for j = 1:1length (v)
z (i,j) = mapFeature (u (i), v(j))*theta;
28
V =
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30
31
32
33
34
end
35
end
z = z'; % important to transpose z before calling contour
% Plot z = 0
% Notice you need to specify the range [0, 0]
contour (u, v, z, [0, 0], 'LineWidth', 2)
36
37
38
39
40 end
41 hold off
42
end](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fdeb17eef-57d7-43a1-af8c-1531444fc3c3%2F4670eb6c-246a-46d6-885a-4810e8af16f1%2F4t41qb_processed.jpeg&w=3840&q=75)
Transcribed Image Text:linspace (-1, 1.5, 50);
= zeros (length (u), length (v) ) ;
% Evaluate z = theta*x over the grid
for i = 1:length (u)
for j = 1:1length (v)
z (i,j) = mapFeature (u (i), v(j))*theta;
28
V =
29
30
31
32
33
34
end
35
end
z = z'; % important to transpose z before calling contour
% Plot z = 0
% Notice you need to specify the range [0, 0]
contour (u, v, z, [0, 0], 'LineWidth', 2)
36
37
38
39
40 end
41 hold off
42
end
![1 Change this code from Matlab to Phython:
응용웅
function plotDecisionBoundary (theta, X, y)
%PLOTDECISIONBOUNDARY Plots the data points X and y into a new figure with
%the decision boundary defined by theta
3
6.
PLOTDECISIONBOUNDARY (theta, X, y) plots the data points with + for the
positive examples and o for the negative examples. X is assumed to be
a either
1) Mx3 matrix, where the first column is an all-ones column for the
intercept.
2) MXN, N>3 matrix, wh
% Plot Data
9.
10
11
re the first column is all-ones
12
13 plotData (X (:, 2:3), y);
14
hold on
15
if size (X, 2) <= 3
16
% only need 2 points to define a line, so choose two endpoints
17
[min (X (:, 2))-2, max (X (:, 2))+2];
% Calculate the decision boundary line
plot_y = (-1./theta (3)). * (theta (2).*plot_x + theta (1));
* Plot, and adjust axes for better viewing
plot (plot_x, plot_y)
% Legend, specific for the exercise
legend ('Admitted', 'Not admitted', 'Decision Boundary')
axis ([30, 100, 30, 100])
18
19
22
23
24
25
else
% Here is the grid range
u = linspace (-1, 1.5, 50);
26
27
olo
olo
olo
olo
olo
ofo
olo
olo
olo
olo
olo
olo
olo
olo
olo
olo
olo
do odo oo do oo
N22 222N 22](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fdeb17eef-57d7-43a1-af8c-1531444fc3c3%2F4670eb6c-246a-46d6-885a-4810e8af16f1%2Fcuf58u6_processed.jpeg&w=3840&q=75)
Transcribed Image Text:1 Change this code from Matlab to Phython:
응용웅
function plotDecisionBoundary (theta, X, y)
%PLOTDECISIONBOUNDARY Plots the data points X and y into a new figure with
%the decision boundary defined by theta
3
6.
PLOTDECISIONBOUNDARY (theta, X, y) plots the data points with + for the
positive examples and o for the negative examples. X is assumed to be
a either
1) Mx3 matrix, where the first column is an all-ones column for the
intercept.
2) MXN, N>3 matrix, wh
% Plot Data
9.
10
11
re the first column is all-ones
12
13 plotData (X (:, 2:3), y);
14
hold on
15
if size (X, 2) <= 3
16
% only need 2 points to define a line, so choose two endpoints
17
[min (X (:, 2))-2, max (X (:, 2))+2];
% Calculate the decision boundary line
plot_y = (-1./theta (3)). * (theta (2).*plot_x + theta (1));
* Plot, and adjust axes for better viewing
plot (plot_x, plot_y)
% Legend, specific for the exercise
legend ('Admitted', 'Not admitted', 'Decision Boundary')
axis ([30, 100, 30, 100])
18
19
22
23
24
25
else
% Here is the grid range
u = linspace (-1, 1.5, 50);
26
27
olo
olo
olo
olo
olo
ofo
olo
olo
olo
olo
olo
olo
olo
olo
olo
olo
olo
do odo oo do oo
N22 222N 22
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