Your task is to determine whether the accelerometer recordings in the test set (test.csv)  belong to the proposed devices in the question set (questions.csv).
The following files are provided:
File name
Description
train.zip
30m samples for training, labeled with DeviceId
test.zip
30m samples for test, split into 90k sequences, labeled with SequenceId
questions.csv
90k questions that match test sequences to DeviceId
train.csv
Field name
Description
T
Unix time (miliseconds since 1/1/1970)
X
Acceleration measured in g on x co-ordinate
Y
Acceleration measured in g on y co-ordinate
Z
Acceleration measured in g on z co-ordinate
DeviceId
Unique Id of the device that generated the samples
test.csv
Field name
Description
T
Unix time (miliseconds since 1/1/1970)
X
Acceleration measured in g on x co-ordinate
Y
Acceleration measured in g on y co-ordinate
Z
Acceleration measured in g on z co-ordinate
SequenceId
Unique sequence number assigned to each question. Each group of samples is labeled with a unique SequenceId. Each SequenceId is matched to a professed DeviceId in the questions.csv file.
questions.csv
Field name
Description
QuestionId
Id of question
SequenceId
Unique number assigned to each sequence of samples
QuizDevice
Professed device that generated the sequence of
accelerometer data in the test file
Data Preparation
After removing from the data set samples from devices with fewer than 6000 samples collected and sequences of samples during periods of rest exceeding 10 seconds, 60 million samples from 387 users were made available for the competition.
Samples from each device were split chronologically into train and test sets, with the earliest samples assigned to the train set.
The test set was demarcated into 90,000 consecutive sequences of 300 samples each from a same device and each sequence assigned a unique Sequence Id.
Each sequence Id was associated with a professed device Id such that in some cases a true device id was assigned and in others a false device id was assigned.