Commit bbed2538 authored by Rakesh MEHTA's avatar Rakesh MEHTA
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parent d2484d4e
...@@ -14,17 +14,18 @@ The weak classfiers associated with these boosting algorithms are ...@@ -14,17 +14,18 @@ The weak classfiers associated with these boosting algorithms are
Check the following reference for the details: Check the following reference for the details:
1) Viola, Paul, and Michael J. Jones. "Robust real-time face detection." 1. Viola, Paul, and Michael J. Jones. "Robust real-time face detection."
International journal of computer vision 57.2 (2004): 137-154. International journal of computer vision 57.2 (2004): 137-154.
2) Saberian, Mohammad J., Hamed Masnadi-Shirazi, and Nuno Vasconcelos. "Taylorboost: 2. Saberian, Mohammad J., Hamed Masnadi-Shirazi, and Nuno Vasconcelos. "Taylorboost:
First and second-order boosting algorithms with explicit margin control." Computer First and second-order boosting algorithms with explicit margin control." Computer
Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on. IEEE, 2011. Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on. IEEE, 2011.
3) Cosmin Atanasoaei, "Multivariate Boosting with Look Up Table for face processing", 3. Cosmin Atanasoaei, "Multivariate Boosting with Look Up Table for face processing",
PhD thesis (2012). PhD thesis (2012).
Testdata: Testdata:
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The test are performed on the MNIST digits dataset. The tests can be mainly divided into The test are performed on the MNIST digits dataset. The tests can be mainly divided into
two categories: two categories:
...@@ -33,13 +34,16 @@ two categories: ...@@ -33,13 +34,16 @@ two categories:
one-vs-one and one-vs-all. Both the boosting algorithm (Gradient Boost and Taylor boost) one-vs-one and one-vs-all. Both the boosting algorithm (Gradient Boost and Taylor boost)
can be used for testing this scenario. can be used for testing this scenario.
2) Multivariate Test: It is the multi class classification problem. All the 10 digit classficaiton 2) Multivariate Test: It is the multi class classification problem. All the 10 digit classfication
is considered in a single test. Only Multivariate Taylor boosting can be used for testing this scenario. is considered in a single test. Only Multivariate Taylor boosting can be used for testing this scenario.
Installation: Installation:
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Once you have downloaded the package use the following two commands to install it: Once you have downloaded the package use the following two commands to install it:
$ python bootstrap.py $ python bootstrap.py
$ ./bin/buildout $ ./bin/buildout
These 2 commands should download and install all non-installed dependencies and These 2 commands should download and install all non-installed dependencies and
...@@ -54,22 +58,22 @@ b) test the dataset for multi class classification. ...@@ -54,22 +58,22 @@ b) test the dataset for multi class classification.
a) The following command will run a single binary test for the digits specified and display the classifcation a) The following command will run a single binary test for the digits specified and display the classifcation
accuracy on the console: accuracy on the console:
$ ./bin/mnist_binary_one.py $ ./bin/mnist_binary_one.py
if you want to see all the option associated with the command type: if you want to see all the option associated with the command type:
$ ./bin/mnist_binary_one.py -h $ ./bin/mnist_binary_one.py -h
To run the tests for all the combination of of ten digits use the following command: To run the tests for all the combination of of ten digits use the following command:
$ ./bin/mnist_binary_all.py $ ./bin/mnist_binary_all.py
This command tests all the possible comniation of digits which results in 45 different binary tests. The This command tests all the possible comniation of digits which results in 45 different binary tests. The
accuracy of individual tests and the final average accuracy of all the tests is displayed on the console. accuracy of individual tests and the final average accuracy of all the tests is displayed on the console.
b) The following command can be used for the multivarite digits test: b) The following command can be used for the multivarite digits test:
$ ./bin/mnist_multi.py $ ./bin/mnist_multi.py
Because of large number of samples and multivariate problem it requires times in days on a normal system. Use -h Because of large number of samples and multivariate problem it requires times in days on a normal system. Use -h
option to see different option available with this command. option to see different option available with this command.
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