Difference between revisions of "Orange: Self-Organizing Map"

Latest revision as of 06:18, 16 April 2020

Sumber: https://docs.biolab.si//3/visual-programming/widgets/unsupervised/selforganizingmap.html

Widget Self-Organizing Map melakukan komputasi dari self-organizing map.

Input

Data: input dataset

Output

Selected Data: instances selected from the plot
Data: data with an additional column showing whether a point is selected

Widget Self-Organizing Map (SOM) adalah jenis dari artificial neural network (ANN) yang di train menggunakan unsupervised learning untuk menghasilkan representasi dua-dimensi, men-discretized dari data. Ini adalah metoda untuk melakukan reduksi dimensi. Widget Self-Organizing Map menggunakan neighborhood function untuk menjaga property topological yang ada di input space.

Pada widget Self-Organizing Map (SOM), titik-titik di grid mewakili contoh data. Secara default, ukuran titik sesuai dengan jumlah instance yang ditunjukkan oleh titik. Poin-poin diwarnai oleh majority class (jika tersedia), sedangkan intensitas warna interior menunjukkan proporsi majority class. Untuk melihat class distribution, pilih opsi Show pie charts option.

Sama seperti widget visualisasi lainnya, widget Self-Organizing Map juga mendukung pemilihan grup secara interaktif. Gunakan tombol Shift untuk memilih grup baru dan Ctr + Shift untuk menambahkan ke grup yang ada.

SOM properties:
- Set the grid type. Options are hexagonal or square grid.
- If Set dimensions automatically is checked, the size of the plot will be set automatically. Alternatively, set the size manually.
- Set the initialization type for the SOM projection. Options are PCA initialization, random initialization and replicable random (random_seed = 0).
- Once the parameters are set, press Start to re-run the optimization.
Set the color of the instances in the plot. The widget colors by class by default (if available).
- Show pie charts turns points into pie-charts that show the distributions of the values used for coloring.
- Size by number of instances scales the points according to the number of instances represented by the point.

Contoh

Widget Self-Organizing Map adalah proyeksi dimensi rendah dari data input. Kita akan menggunakan brown-selected data dan menampilkan instance data dalam proyeksi 2-D. Dalam contoh di bawah ini, sepertinya ketiga jenis gen terpisah dengan baik. Kita dapat memilih subset dari grid dan menampilkannya di widget Data Table.

Referensi

https://docs.biolab.si//3/visual-programming/widgets/unsupervised/selforganizingmap.html

Pranala Menarik

Orange

@@ Line 3: / Line 3: @@
-Computation of a self-organizing map.
+Widget Self-Organizing Map melakukan komputasi dari self-organizing map.
-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
-A self-organizing map (SOM) is a type of artificial neural network (ANN) that is trained using unsupervised learning to produce a two-dimensional, discretized representation of the data. It is a method to do dimensionality reduction. Self-organizing maps use a neighborhood function to preserve the topological properties of the input space.
+Widget Self-Organizing Map (SOM) adalah jenis dari artificial neural network (ANN) yang di train menggunakan unsupervised learning untuk menghasilkan representasi dua-dimensi, men-discretized dari data. Ini adalah metoda untuk melakukan reduksi dimensi. Widget Self-Organizing Map menggunakan neighborhood function untuk menjaga property topological yang ada di input space.
-The points in the grid represent data instances. By default, the size of the point corresponds to the number of instances represented by the point. The points are colored by majority class (if available), while the intensity of interior color shows the proportion of majority class. To see the class distribution, select Show pie charts option.
+Pada widget Self-Organizing Map (SOM), titik-titik di grid mewakili contoh data. Secara default, ukuran titik sesuai dengan jumlah instance yang ditunjukkan oleh titik. Poin-poin diwarnai oleh majority class (jika tersedia), sedangkan intensitas warna interior menunjukkan proporsi majority class. Untuk melihat class distribution, pilih opsi Show pie charts option.
-Just like other visualization widgets, Self-Organizing Maps also supports interactive selection of groups. Use Shift key to select a new group and Ctr+Shift to add to the existing group.
+Sama seperti widget visualisasi lainnya, widget Self-Organizing Map juga mendukung pemilihan grup secara interaktif. Gunakan tombol Shift untuk memilih grup baru dan Ctr + Shift untuk menambahkan ke grup yang ada.
-[[File:Self-Organizing Map-stamped.png|center|200px|thumb]]
+[[File:Self-Organizing Map-stamped.png|center|600px|thumb]]
-    SOM properties:
+* SOM properties:
-        Set the grid type. Options are hexagonal or square grid.
+** Set the grid type. Options are hexagonal or square grid.
-        If Set dimensions automatically is checked, the size of the plot will be set automatically. Alternatively, set the size manually.
+** If Set dimensions automatically is checked, the size of the plot will be set automatically. Alternatively, set the size manually.
-        Set the initialization type for the SOM projection. Options are PCA initialization, random initialization and replicable random (random_seed = 0).
+** Set the initialization type for the SOM projection. Options are PCA initialization, random initialization and replicable random (random_seed = 0).
-        Once the parameters are set, press Start to re-run the optimization.
+** Once the parameters are set, press Start to re-run the optimization.
-    Set the color of the instances in the plot. The widget colors by class by default (if available).
+* Set the color of the instances in the plot. The widget colors by class by default (if available).
-        Show pie charts turns points into pie-charts that show the distributions of the values used for coloring.
+** Show pie charts turns points into pie-charts that show the distributions of the values used for coloring.
-        Size by number of instances scales the points according to the number of instances represented by the point.
+** Size by number of instances scales the points according to the number of instances represented by the point.
 ==Contoh==
-Self-organizing maps are low-dimensional projections of the input data. We will use the brown-selected data and display the data instance in a 2-D projection. Seems like the three gene types are well-separated. We can select a subset from the grid and display it in a Data Table.
+Widget Self-Organizing Map adalah proyeksi dimensi rendah dari data input. Kita akan menggunakan brown-selected data dan menampilkan instance data dalam proyeksi 2-D. Dalam contoh di bawah ini, sepertinya ketiga jenis gen terpisah dengan baik. Kita dapat memilih subset dari grid dan menampilkannya di widget Data Table.
-[[File:Self-Organizing Map Example.png|center|200px|thumb]]
+[[File:Self-Organizing Map Example.png|center|600px|thumb]]
 ==Referensi==