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    F-score (also known as F1-score) is a metric used to evaluate the performance of a binary classification model. It is a harmonic mean of precision and recall.

    Precision is the ratio of true positives to the total number of positive predictions, while recall is the ratio of true positives to the total number of actual positive instances in the data.

    The F-score is calculated by taking the harmonic mean of precision and recall. It is a way to balance the trade-off between precision and recall.

    The formula for F-score is:

    F-score = 2 * (precision * recall) / (precision + recall)

    The F-score ranges from 0 to 1, with 1 being the best score. A high F-score indicates that the model has high precision and recall and is performing well in correctly identifying positive instances.

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    Dr. Ujjal Marjit leads the Centre for Information Resource Management of the University of Kalyani, India. He received his bachelor honours degree from Visva Bharati, Central University and Master in Computer Application from Jadavpur University, India.He did his BLISc and MLISc from Madurai Kamraj University, India. He obtained his PhD in Computer Science and Engineering from University of Kalyani. He was also a visiting researcher at Norwegian University of Science and Technology (NTNU), Norway. Dr. Marjit was a member of the Association for Computing Machinery (ACM), USA. He has coauthored several book chapters and over 70 research publications in various International Journals and Conferences. Dr. Marjit attended many national and international conferences in India and abroad ( Germany, London, Finland, Norway, Netherlands). He has been working in University since 2001.