Browsing by Subject "Random forest regressor"
Now showing items 1-4 of 4
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Into the heart of Bangla speech: advancing speech sentiment recognition with semi-supervised multimodal machine learning model leveraging an iterative SHAP-based feature selection
(Brac University, 2024-06)Automatic sentiment recognition from speech data is crucial for various applications. As AI has grown in popularity, the application of the importance of speech sentiment analysis is increasing along with the amount of ... -
A performance comparison between machine learning models on zero-day attack detection
(Brac University, 2021-01)Traditional IDS has been shielding against cyber threats for many years but it falls short on detecting zero-day attacks. These are the attacks that are unique with unknown attack patterns and mutating attack signatures ... -
Unleashing potential: a data-driven exploration of identifying player potentialities through advanced analytics in sports
(Brac University, 2024-01)In this project, we delve deeper into the complex area of predicting a potential replacement of a footballer of a specific position. For that, we used multiple machine learning models on the Sofifa dataset. Our analysis ... -
Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations
(Brac University, 2024-06)The research provides a deep exploration of cryptocurrency price dynamics by blending technical analysis, sentiment analysis, and backtesting, aiming to reveal the hidden patterns, drivers, and irregularities in their ...
