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    Machine learning classification techniques for non-intrusive load monitoring 

    Chung, Jefferson (2016-10-01)
    Non-intrusive load monitoring is the concept of determining the operational loads using single-point sensing. The features contained within the electrical load’s signal are used to identify a unique signature which is ...
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    Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers 

    Gillett, Jonathan (2016-10-01)
    The ability to predict financial markets has tremendous potential to limit exposure to risk and provide better assurances of annualized gains. In this thesis, a model for predicting the future daily price of Bitcoin is ...
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    Machine learning classifiers for critical cardiac conditions 

    Gilani, Mehrin (2016-04-01)
    Cardiac diseases are one of the leading causes of death in Canada. Current methods of diagnosing cardiac conditions require a manual and visual analysis of ECG and heart rate (RR interval) data. In this thesis, novel ...

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    AuthorChung, Jefferson (1)Gilani, Mehrin (1)Gillett, Jonathan (1)Subject
    Machine learning (3)
    Atrial fibrillation (1)Bitcoin (1)Co-testing (1)Congestive heart failure (1)Electrocardiogram (ECG) (1)Heart rate variability (1)Non-intrusive load monitoring (1)Predictive model (1)... View MoreDate Issued
    2016 (3)
    Has File(s)Yes (3)

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