Nurah.lee

 Since your dataset was reduced from all attributes to only two (Status & Target) , you should compare the evaluation metrics (e.g., accuracy, precision, recall, F1-score) of the classification models before and after reduction. 1. Collect Evaluation Results from Weka After running classification models on both datasets ( full dataset and reduced dataset ), record the following metrics: Accuracy (%) Precision (%) Recall (%) F1-Score (%) Cross-validation (k=10, k=20) results Percentage split (70:30, 80:20) results 2. Organizing Data in Excel Step 1: Create a Table in Excel Format your results into a table: Dataset Model Accuracy (%) Precision (%) Recall (%) F1-Score (%) Full (Before Reduction) J48 85 84 83 84 Full (Before Reduction) Random Forest 88 87 86 87 Reduced (After Reduction) J48 75 74 73 74 Reduced (After Reduction) Random Forest 78 77 76 77 Step 2: Insert a Bar Chart Select the table data. Go to Insert →...

Sam Kas Co is a shipping company that owns six ships. In emergency cases, the company will release the coordinates of each ship to other ships. The nearest ship will be assigned to help the trouble ship. Assume now that a ship. MayDay with coordinate (10,5), is in trouble. Table below shows the current coordinates for all the other ships.   Ship Name Coordinate X Coordinate Y Air 18 11 Bay 7 1 Cell 3 7 Dream 11 4 Eve 6 6   1.       Write a pseudocode that receives the coordinate of the troubled ships and a list of other ships’ coordinates. The algorithm will return coordinate that of the nearest ship to the troubled ship.   FindNearestShip(troubleShipX, troubleShipY, ship_list)       minDistance = INFINITE   ...