To study and implement the K-NN Classifier for pattern recognition and prediction
Initiate the process by clicking on the CREATE tab.
Now, select whether you want to use a predefined dataset or create your own dataset.
- If, predefined data selected then jump to step 5.
- Otherwise, continue to the next step(3).
Input the values for Sepal Length and Sepal Width, and select a Species from the attributes section. Afterward, click on the ADD button.
Repeat the third step up to 12 times for data augmentation.
Progress to the next stage by clicking on the NEXT button.
Record the values of Sepal Length and Sepal Width into the Testing dataset, and then add them by clicking on the ADD button.
Navigate to the next phase by clicking on the NEXT button.
Choose the desired value for K, submit your selection by clicking the SUBMIT button, and then advance by clicking the NEXT button.
Determine the Euclidean distance between your new data point and the dataset by utilizing the DISTANCE button located below the table.
Establish the order of the distance (i.e., its position in the sorted list) by clicking on the RANK button.
Continue the analysis by clicking on the NEXT button to assess the category of the Testing data.
Visualize the K-Nearest Neighbors on the graph by clicking on the PLOT button.