Orange: Silhouette Plot - Revision history

Onnowpurbo at 04:13, 9 April 2020

2020-04-09T04:13:22Z

Onnowpurbo: /* Contoh */

2020-04-09T04:06:46Z

Contoh

Onnowpurbo: /* Output */

2020-04-09T04:06:27Z

Output

Onnowpurbo at 02:17, 28 January 2020

2020-01-28T02:17:54Z

Onnowpurbo at 01:11, 23 January 2020

2020-01-23T01:11:43Z

Onnowpurbo: Created page with "Sumber: https://docs.biolab.si//3/visual-programming/widgets/visualize/silhouetteplot.html A graphical representation of consistency within clusters of data. Inputs Da..."

2020-01-12T12:17:14Z

Created page with "Sumber: https://docs.biolab.si//3/visual-programming/widgets/visualize/silhouetteplot.html A graphical representation of consistency within clusters of data. Inputs Da..."

New page

Sumber: https://docs.biolab.si//3/visual-programming/widgets/visualize/silhouetteplot.html

A graphical representation of consistency within clusters of data.

Inputs

Data: input dataset

Outputs

Selected Data: instances selected from the plot

Data: data with an additional column showing whether a point is selected

The Silhouette Plot widget offers a graphical representation of consistency within clusters of data and provides the user with the means to visually assess cluster quality. The silhouette score is a measure of how similar an object is to its own cluster in comparison to other clusters and is crucial in the creation of a silhouette plot. The silhouette score close to 1 indicates that the data instance is close to the center of the cluster and instances possessing the silhouette scores close to 0 are on the border between two clusters.

../../_images/SilhouettePlot-stamped.png

Choose the distance metric. You can choose between:

Euclidean (“straight line” distance between two points)

Manhattan (the sum of absolute differences for all attributes)

Cosine (1 - cosine of the angle between two vectors)

Select the cluster label. You can decide whether to group the instances by cluster or not.

Display options:

Choose bar width.

Annotations: annotate the silhouette plot.

Save Image saves the created silhouette plot to your computer in a .png or .svg format.

Produce a report.

Output:

Add silhouette scores (good clusters have higher silhouette scores)

By clicking Commit, changes are communicated to the output of the widget. Alternatively, tick the box on the left and changes will be communicated automatically.

The created silhouette plot.

Example

In the snapshot below, we have decided to use the Silhouette Plot on the iris dataset. We selected data instances with low silhouette scores and passed them on as a subset to the Scatter Plot widget. This visualization only confirms the accuracy of the Silhouette Plot widget, as you can clearly see that the subset lies in the border between two clusters.

../../_images/SilhouettePlot-Example.png

If you are interested in other uses of the Silhouette Plot widget, feel free to explore our blog post.

==Referensi==

* https://docs.biolab.si//3/visual-programming/widgets/visualize/silhouetteplot.html

==Pranala Menarik==

* [[Orange]]

@@ Line 2: / Line 2: @@
-A graphical representation of consistency within clusters of data.
+Widget Silhouette Plot menampilkan representasi grafis akan inkonsistensi dalam data cluster.
 ==Input==
@@ Line 13: / Line 14: @@
   Data: data with an additional column showing whether a point is selected
-The Silhouette Plot widget offers a graphical representation of consistency within clusters of data and provides the user with the means to visually assess cluster quality. The silhouette score is a measure of how similar an object is to its own cluster in comparison to other clusters and is crucial in the creation of a silhouette plot. The silhouette score close to 1 indicates that the data instance is close to the center of the cluster and instances possessing the silhouette scores close to 0 are on the border between two clusters.
+Widget Silhouette Plot menawarkan representasi grafis akan konsistensi dalam data cluster dan memberi pengguna sarana untuk menilai kualitas cluster secara visual. Silhouette score adalah ukuran seberapa mirip suatu objek dengan clusternya sendiri dibandingkan dengan cluster lain dan sangat penting dalam pembuatan Silhouette plot. Silhouette score mendekati 1 menunjukkan bahwa instance data dekat dengan pusat cluster dan instance yang memiliki Silhouette score mendekati 0 berada di perbatasan antara dua cluster.
 [[File:SilhouettePlot-stamped.png|center|600px|thumb]]
@@ Line 40: / Line 41: @@
 ==Contoh==
-In the snapshot below, we have decided to use the Silhouette Plot on the iris dataset. We selected data instances with low silhouette scores and passed them on as a subset to the Scatter Plot widget. This visualization only confirms the accuracy of the Silhouette Plot widget, as you can clearly see that the subset lies in the border between two clusters.
+Dalam workflow di bawah ini, kita akan menggunakan widget Silhouette Plot pada dataset iris. Kita memilih instance data dengan silhouette score rendah dan meneruskannya subset dari widget Scatter Plot. Visualisasi ini hanya mengkonfirmasi keakuratan widget Silhouette Plot, karena anda dapat dengan jelas melihat bahwa subset terletak di perbatasan antara dua cluster.
 [[File:SilhouettePlot-Example.png|center|600px|thumb]]

@@ Line 42: / Line 42: @@
 In the snapshot below, we have decided to use the Silhouette Plot on the iris dataset. We selected data instances with low silhouette scores and passed them on as a subset to the Scatter Plot widget. This visualization only confirms the accuracy of the Silhouette Plot widget, as you can clearly see that the subset lies in the border between two clusters.
-[[File:SilhouettePlot-Example.png|center|200px|thumb]]
+[[File:SilhouettePlot-Example.png|center|600px|thumb]]
 ==Referensi==

@@ Line 15: / Line 15: @@
 The Silhouette Plot widget offers a graphical representation of consistency within clusters of data and provides the user with the means to visually assess cluster quality. The silhouette score is a measure of how similar an object is to its own cluster in comparison to other clusters and is crucial in the creation of a silhouette plot. The silhouette score close to 1 indicates that the data instance is close to the center of the cluster and instances possessing the silhouette scores close to 0 are on the border between two clusters.
-[[File:SilhouettePlot-stamped.png|center|200px|thumb]]
+[[File:SilhouettePlot-stamped.png|center|600px|thumb]]
 * Choose the distance metric. You can choose between:

@@ Line 4: / Line 4: @@
 A graphical representation of consistency within clusters of data.
-Inputs
+==Input==
-    Data: input dataset
+ Data: input dataset
-Outputs
+==Output==
-    Selected Data: instances selected from the plot
+ Selected Data: instances selected from the plot
-    Data: data with an additional column showing whether a point is selected
+ Data: data with an additional column showing whether a point is selected
 The Silhouette Plot widget offers a graphical representation of consistency within clusters of data and provides the user with the means to visually assess cluster quality. The silhouette score is a measure of how similar an object is to its own cluster in comparison to other clusters and is crucial in the creation of a silhouette plot. The silhouette score close to 1 indicates that the data instance is close to the center of the cluster and instances possessing the silhouette scores close to 0 are on the border between two clusters.
@@ Line 17: / Line 17: @@
 [[File:SilhouettePlot-stamped.png|center|200px|thumb]]
-    Choose the distance metric. You can choose between:
+* Choose the distance metric. You can choose between:
-    Display options:
+** Euclidean (“straight line” distance between two points)
-        Choose bar width.
+* Select the cluster label. You can decide whether to group the instances by cluster or not.
-        Annotations: annotate the silhouette plot.
+* Display options:
-    Produce a report.
+** Choose bar width.
-    Output:
+* Save Image saves the created silhouette plot to your computer in a .png or .svg format.
-        Add silhouette scores (good clusters have higher silhouette scores)
+* Output:
-        By clicking Commit, changes are communicated to the output of the widget. Alternatively, tick the box on the left and changes will be communicated automatically.
-    The created silhouette plot.
+** Add silhouette scores (good clusters have higher silhouette scores)
 ==Contoh==