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About Human Activity Classification
This document discusses human activity classification using machine learning techniques. It compares logistic regression, support vector machines, decision trees, and neural networks on a dataset containing sensor data from wearable devices. The dataset contains over 1.9 million data points measuring 12 different human activities. The paper finds that deep learning techniques like convolutional neural networks achieved the highest classification accuracy above 95% for recognizing human activities.
Detailed Information
Author: | ['nikhil singh'] |
---|---|
Publication Year: | 2021 |
Pages: | 6 |
Language: | English |
Format: | |
Price: | FREE |
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