QMAK: Interacting with Machine Learning Models and Visualizing Classification Process

In various classification problems beside high accuracy data analysts expect often understanding and certain insight into the process of classification. To help them understand why a trained model selects a particular decision, how confident it is in the assigned decision, and to enable interactive improvement of trained models we present QMAK. The tool visualizes not only classification models but also the processes classifying individual objects. Five classical machine learning models and their classification process are visualized with QMAK: neural network, decision tree, k nearest neighbors, classifier based on principal component analysis (PCA) and rough set based classifier. QMAK provides also exemplary functions enabling users to modify trained models interactively.

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1. Main Track Short Papers

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2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).