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What this article shares to you is about how to analyze the K-Distance analysis chart of the XGIS tool in DBSCAN, the editor thinks it is very practical, so I share it with you to learn. I hope you can get something after reading this article.

How to define the two parameters of DBSCAN, namely the search radius and the minimum number of points. It is very friendly to recommend a K-Distance analysis method.

The principle is as follows:

Suppose there are a total of N spatial objects to be clustered.

First of all, the minimum points can only be tried! Feel free to try, such as 2pm, 10pm, 20pm, etc.

For the minimum number of points (also known as K value) of an attempt, the distance between each spatial object and its nearest K spatial object is calculated, from which N distance values are obtained.

Put the N distance values in order from small to large, draw a graph to see where the most dramatic change in the curve (usually refers to the steepest position of the curve), then this position may be the best search radius.

See how our updated software is implemented.

In the new window, we add buttons.

After clicking, the following interface opens:

In the upper left corner, you can try different K values, modify the K value, click, you can get two analysis diagrams.

The figure above shows the N K nearest distance curves after sorting.

The following figure shows the difference between the front and back distance values in the above curve.

From the difference map, the position with the most drastic change (the highest wave peak) can be found, and the recommended search radius can be obtained by taking the average distance between the two K nearest distances.

Click to pass this value directly to the main interface.

There is a method, but please note:

Obviously, this seems to be a simple method. No matter what K value you choose, we can give you a recommended search radius according to the following figure (difference map), but please remember

The above is how to analyze the K-Distance analysis diagram of the XGIS tool in DBSCAN. The editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

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