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November 6, 2011 14:24
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log_regression
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| from numpy import loadtxt, where | |
| from pylab import scatter, show, legend, xlabel, ylabel | |
| #load the dataset | |
| data = loadtxt('ex2data1.txt', delimiter=',') | |
| X = data[:, 0:2] | |
| y = data[:, 2] | |
| pos = where(y == 1) | |
| neg = where(y == 0) | |
| scatter(X[pos, 0], X[pos, 1], marker='o', c='b') | |
| scatter(X[neg, 0], X[neg, 1], marker='x', c='r') | |
| xlabel('Exam 1 score') | |
| ylabel('Exam 2 score') | |
| legend(['Not Admitted', 'Admitted']) | |
| show() |
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@arjunchatterjee196 and @sshaky2,
you can find the data in the coursera Machine Learning Course, or in this link:
https://github.com/vinipachecov/machine-learning-coursera-1/tree/master/Week%203%20Assignments/Logistic%20Regression%20and%20Regularization/mlclass-ex2