[Weka][Machine Learning][Kmeans]Weka labelling result of Kmeans

### The Step-by-Step Process

1. **Run your Clusterer:**

* Go to the **Cluster** tab.

* Select **SimpleKMeans** and configure your  (number of clusters).

* Run the algorithm. Ensure it completes successfully.

2. **Add the Labels via Filter:**

* Switch back to the **Preprocess** tab.

* Click **Choose** under the Filters section.

* Navigate to: `filters` -> `unsupervised` -> `attribute` -> **AddCluster**.

3. **Configure the Filter:**

* Click on the **AddCluster** text to open its configuration box.

* In the `clusterer` field, click "Choose" and select **SimpleKMeans** again (ensure the settings match what you used in the Cluster tab).

* Click **OK**.

4. **Apply and Save:**

* Click **Apply**. You will see a new attribute appear at the end of your attribute list, typically named "cluster."

* Click **Save...** to export your new labeled dataset as an `.arff` or `.csv` file.

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### Pro-Tips for Labeling

* **The "Ignored" Attributes:** If you want to cluster based on certain features but keep an ID or Name column in the final file, make sure to use the `ignoredAttributeIndices` property within the SimpleKMeans settings inside the **AddCluster** filter.

* **Result Verification:** Before saving, you can click the **Edit...** button in the Preprocess tab to view the data table and confirm that the cluster assignments look correct (e.g., Cluster 0, Cluster 1, etc.).

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