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bag-of-words representation for biomedical time series classificaiton
by Jin
a simple yet effective bag-of-words representation for biomedical time series, such as EEG and ECG.
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| config_file_128_1000.m |
%%%%% Configuration file for bag-of-words representation for biomedical time series%%%%%%
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%%% DIRECTORIES - please change if copying the code to a new location
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%% Directory holding all the experiment image frames
DATA_DIR = './data/original_data/';
%% Directory holding the codebook, i.e., the k-mean clusters
CODEBOOK_DIR = './data/codebook/';
%% Feature directory - holds all features
FEATURE_DIR = './data/feature/';
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%%% dataset parameters
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%% number of classes
num_class = 5;
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%%% bag-of-words parameters
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%% Transform
transform = 'wavelet';
%% length of subsequences
sub_length = 128;
%% over points between slideing window
inter_point = 4;
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%%% codebook parameters
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%% size of codebook
VQ.Codebook_Size = 1000;
%% Max number of k-means iterations
VQ.Max_Iterations = 20;
%% Verbsoity of Mark's code
VQ.Verbosity = 0;
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