The program will print a formatted matrix to the console along with a summary report for each class. Advanced Analysis Features
The file is the Windows distribution for Confusion v0.5 , a specialized machine learning tool used to generate and analyze confusion matrices .
Detailed performance reports including Sensitivity, Specificity, Precision, and F-score. Core Components & Metrics Confusion-0.5-win.zip
Below is a detailed report on the software, its core functionality, and how to utilize it for performance evaluation in classification tasks.
The tool processes classification data to build a matrix where rows represent actual classes and columns represent predicted classes. Definition Importance Correctly predicted positive instances. Measures successful identification. False Positives (FP) Incorrectly predicted positive instances. Indicates "Type I" error (false alarm). False Negatives (FN) Missed positive instances. Indicates "Type II" error (missed detection). Precision Shows how reliable the positive predictions are. Recall (Sensitivity) Shows how many actual positives the model found. Usage Instructions The program will print a formatted matrix to
Create a text or CSV file where each line contains the Actual Class followed by the Predicted Class (e.g., Class_A Class_B ).
By highlighting high values in non-diagonal cells, the tool helps identify which specific classes the model is frequently "confusing" with others. Core Components & Metrics Below is a detailed
To generate a report using the Windows version, follow these steps: