click here to download project abstract of supervised machine learning algorithm
At DataPro, we provide final year projects with source code in python for computer science students in Hyderabad , Visakhapatnam.
ABSTRACT
Introduction: In the wake of the COVID-19 pandemic, swift and accurate identification of infected individuals is paramount for effective containment and treatment. Supervised machine learning algorithms offer a promising approach to discerning COVID-19 cases from other respiratory illnesses with speed and precision.
Understanding Supervised Machine Learning: Supervised machine learning involves training a model on labeled data to make predictions or classifications.
Data Collection and Feature Selection: so The first step involves gathering a diverse dataset comprising clinical symptoms, demographic information, and diagnostic test results. Feature selection plays a crucial role in enhancing model performance by identifying the most relevant attributes for classification.
Preprocessing and Cleaning: Cleaning the dataset mitigates the risk of biased or erroneous predictions.
Performance Metrics: Metrics such as accuracy, precision, recall, and F1-score are employed to assess the model’s performance. These metrics provide insights into the algorithm’s ability to correctly identify COVID-19 cases while minimizing false positives and false negatives.
Conclusion: thus Supervised machine learning algorithms present a powerful tool in the fight against COVID-19 by facilitating rapid and reliable identification of infected individuals.
