Browsing by Subject "Random forest regressor"
Now showing items 1-7 of 7
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Advanced video analytic system for posture and activity recognition: leveraging MediaPipe, CNN-LSTM, and ensemble learning for fall and unstable motion detection
(BRAC University, 2024-10)Human posture detection and classification are vital in monitoring activities, especially in health and safety contexts, such as fall detection in elderly care. This thesis presents a comparative study of two machine ... -
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 ... -
Loan approval prediction using machine learning algorithms
(BRAC University, 2024-10)This research describes the potential of several classifiers of classical machine learning and architecture of deep neural networks when predicting the status of a loan application. The data set of 613 observations and ... -
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 ... -
Sales forecasting using machine learning
(BRAC University, 2024-10)In today’s aggressive and fast-paced economy, the ability to forecast sales accurately and effectively denotes a proper utilization of the available resources in planning. Typical sales forecasting methods fail quite ... -
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 ...
