Electrocardiography (ECG) is a transthoracic interpretation of the electrical activity of the heart over a period of time, which can reflect the physical condition of a heart. We carry a series of experiments based on ten sets of different ECG data. First, we pre-process the raw data with data processing technology, and then we use the feature extraction technology of PCA and ICA to get a new feature space. At last we use support vector machine to train a model which can and finally predict and classify the unlabeled ECG data. We validate and optimize the model by evaluating its performance when training it.

get_test_data.m
ica_classification.m
ica_predict_on_test.m
pca_classification.m
predict_on_test.m
train_test_data.m

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．