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Implemented Divide and Conquer-Based 1D CNN approach that identifies the static and dynamic activities separately. The final stacked model gave an accuracy of 93% without the test data sharpening process.
This repository contains code related to identifying malicious sensor nodes using the SensorNetGuard Dataset. The code implements three models: Long Short-Term Memory(LSTM), Gated Recurrent Unit(GRU) and One-Dimensional Convolutional Neural Network (1D-CNN).
This research study employs a mixed-methods approach to analyze the global growth of Nigerian music, utilizing data from Spotify, UK Charts, and the Billboard Hot 100. Various data analysis techniques like descriptive statistics and sentiment analysis are applied, alongside predictive models like 1D CNN and Decision Trees.