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Accelerometer-Biometric

Recognize users of mobile devices from accelerometer data ( Accelerometer Biometric Competition on kaggle)

A course Project for 'CS 725: Foundations of Machine Learning'

#Description: You can find the description of problem statement at https://www.kaggle.com/c/accelerometer-biometric-competition

#How To Run the Code:

Assumption: You have train.csv and test.csv in the same folder as other project files

  1. Run device_count.py

  2. Run extractMeanVar.py

  3. Run trimmingdata.py

  4. Now you can execute any classifier code. Just look for the required files are there in the same folder.

#Our Approaches We devised following approaches for solving the problem:

  1. Naive Bayes

  2. Nearest Neighbors

  3. Quadratic Discriminative Analysis ( Similar to LDA)

  4. Support Vector Machines

#File related to each approach:

1] Naive Bayes

1. extractMeanVar.py
2. naive_bayes.py
3. naive_bayes_Random.py

2] Nearest Neighbors

1. trimmingdata.py
2. device_count.py
3. KNearestNeighbour.py

3] Quadratic Discriminative Analysis ( Similar to LDA)

1. qda.py

4] Support Vector Machines

1. svm_mean.py
2. svm_modified.py

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Recognize users of mobile devices from accelerometer data ( Accelerometer Biometric Competition on kaggle)

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