Orange: Neighbors - Revision history

Onnowpurbo: /* Output */

2020-04-20T04:24:11Z

Output

← Older revision		Revision as of 04:24, 20 April 2020
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	Neighbors: A data table of nearest neighbors according to reference.		Neighbors: A data table of nearest neighbors according to reference.

	Widget Neighbors menghitung tetangga terdekat untuk referensi yang diberikan dan untuk ukuran jarak tertentu. Referensi dapat berupa satu ~~instance~~ atau lebih instance. Dalam kasus dengan satu referensi, widget Neighbors output n instance dari data di mana n diatur oleh opsi Number of neighbors pada widget Neighbors. Ketika referensi mengandung lebih banyak instance, widget Neighbors menghitung jarak gabungan untuk setiap instance data sebagai jarak minimum untuk setiap referensi. Widget Neighbors akan menghasilkan n instance data dengan jarak gabungan terendah.		Widget Neighbors menghitung tetangga terdekat untuk referensi yang diberikan dan untuk ukuran jarak tertentu. Referensi dapat berupa satu atau lebih instance. Dalam kasus dengan satu referensi, widget Neighbors output n instance dari data di mana n diatur oleh opsi Number of neighbors pada widget Neighbors. Ketika referensi mengandung lebih banyak instance, widget Neighbors menghitung jarak gabungan untuk setiap instance data sebagai jarak minimum untuk setiap referensi. Widget Neighbors akan menghasilkan n instance data dengan jarak gabungan terendah.

	[[File:Neighbours-stamped.png\|center\|200px\|thumb]]		[[File:Neighbours-stamped.png\|center\|200px\|thumb]]

Onnowpurbo: /* Contoh */

2020-04-11T13:43:45Z

Contoh

← Older revision		Revision as of 13:43, 11 April 2020
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	==Contoh==		==Contoh==

	Pada contoh ~~pertama~~, kita menggunakan data iris dan meneruskannya ke Neighbors dan Data Table. Dalam ~~Tabel~~ Data, kita memilih contoh iris, yang akan berfungsi sebagai referensi kita, artinya kita ingin mengambil 10 contoh terdekat ke instance data terpilih. Kita menghubungkan Data Table ke Neighbors juga.		Pada contoh ini, kita menggunakan data iris dan meneruskannya ke widget Neighbors dan widget Data Table. Dalam widget Data Table, kita memilih contoh iris, yang akan berfungsi sebagai referensi kita, artinya kita ingin mengambil 10 contoh terdekat ke instance data terpilih. Kita menghubungkan widget Data Table ke widget Neighbors juga.

	Kita dapat mengamati hasil neighbor computation di Data Table (1), di mana kita dapat melihat 10 gambar terdekat dengan bunga iris pilihan kita.		Kita dapat mengamati hasil neighbor computation di widget Data Table (1), di mana kita dapat melihat 10 gambar terdekat dengan bunga iris pilihan kita.

	[[File:Neighbours-example1.png\|center\|~~200px~~\|thumb]]		[[File:Neighbours-example1.png\|center\|600px\|thumb]]

	Sekarang ubah selection Data Table menjadi multiple examples. Sebagai hasilnya, kita mendapatkan instance dengan jarak gabungan terdekat ke referensi. Metode ini menghitung jarak gabungan sebagai jarak minimum untuk setiap referensi.		Sekarang ubah selection pada widget Data Table menjadi multiple examples. Sebagai hasilnya, kita mendapatkan instance dengan jarak gabungan terdekat ke referensi. Metode ini menghitung jarak gabungan sebagai jarak minimum untuk setiap referensi.

	[[File:Neighbours-example-multiple.png\|center\|~~200px~~\|thumb]]		[[File:Neighbours-example-multiple.png\|center\|600px\|thumb]]

	Contoh ~~lain~~ membutuhkan ~~pemasangan~~ add-on Image Analytics. Kita me-load 15 lukisan dari pelukis terkenal dengan Import Images ~~widget~~ dan menyerahkannya ke Image Embedding, dimana kita memilih ~~Pelukis~~.		Contoh ini, kita membutuhkan tambahan add-on Image Analytics. Kita me-load 15 lukisan dari pelukis terkenal dengan widget Import Images dan menyerahkannya ke widget Image Embedding, dimana kita memilih Painter.

	Maka prosedurnya sama seperti di atas. Kita meneruskan embedded images ke Image Viewer dan memilih lukisan dari Monet untuk dijadikan gambar referensi kita. Kita meneruskan gambar ke Neighbors, tempat ~~kami~~ mengatur ukuran jarak ke cosinus, menandai agar exclude dari referensi dan menset ke neighbour ke 2. Ini memungkinkan kita untuk menemukan actual closest neighbor dengan lukisan referensi dan mengamati mereka berdampingan di Image Viewer (1).		Maka prosedurnya sama seperti di atas. Kita meneruskan embedded images ke widget Image Viewer dan memilih lukisan dari Monet untuk dijadikan gambar referensi kita. Kita meneruskan gambar ke widget Neighbors, tempat kita mengatur ukuran jarak ke cosinus, menandai agar exclude dari referensi dan menset ke neighbour ke 2. Ini memungkinkan kita untuk menemukan actual closest neighbor dengan lukisan referensi dan mengamati mereka berdampingan di widget Image Viewer (1).

	[[File:Neighbours-example2.png\|center\|~~200px~~\|thumb]]		[[File:Neighbours-example2.png\|center\|600px\|thumb]]

	==Referensi==		==Referensi==

Onnowpurbo: /* Output */

2020-04-11T13:40:44Z

Output

← Older revision		Revision as of 13:40, 11 April 2020
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	Neighbors: A data table of nearest neighbors according to reference.		Neighbors: A data table of nearest neighbors according to reference.

	Widget Neighbors menghitung tetangga terdekat untuk referensi yang diberikan dan untuk ukuran jarak tertentu. Referensi dapat berupa satu atau lebih instance. Dalam kasus dengan satu ~~widget~~ referensi, output ~~terdekat~~ n ~~contoh~~ dari data di mana n diatur oleh opsi Number of neighbors ~~option~~ pada widget. Ketika referensi mengandung lebih banyak instance widget menghitung jarak gabungan untuk setiap instance data sebagai jarak minimum untuk setiap referensi. ~~Output widget dan~~ instance data dengan jarak gabungan terendah.		Widget Neighbors menghitung tetangga terdekat untuk referensi yang diberikan dan untuk ukuran jarak tertentu. Referensi dapat berupa satu instance atau lebih instance. Dalam kasus dengan satu referensi, widget Neighbors output n instance dari data di mana n diatur oleh opsi Number of neighbors pada widget Neighbors. Ketika referensi mengandung lebih banyak instance, widget Neighbors menghitung jarak gabungan untuk setiap instance data sebagai jarak minimum untuk setiap referensi. Widget Neighbors akan menghasilkan n instance data dengan jarak gabungan terendah.

	[[File:Neighbours-stamped.png\|center\|200px\|thumb]]		[[File:Neighbours-stamped.png\|center\|200px\|thumb]]

Onnowpurbo at 13:37, 11 April 2020

2020-04-11T13:37:41Z

← Older revision		Revision as of 13:37, 11 April 2020
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	Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html		Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html

	~~Hitung~~ tetangga terdekat dalam data sesuai dengan referensi.		Widget Neighbors menghitung tetangga terdekat dalam data sesuai dengan referensi.

	==Input==		==Input==
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	Neighbors: A data table of nearest neighbors according to reference.		Neighbors: A data table of nearest neighbors according to reference.

	Neighbors ~~widget~~ menghitung tetangga terdekat untuk referensi yang diberikan dan untuk ukuran jarak tertentu. Referensi dapat berupa satu atau lebih instance. Dalam kasus dengan satu widget referensi, output terdekat n contoh dari data di mana n diatur oleh opsi Number of neighbors option pada widget. Ketika referensi mengandung lebih banyak instance widget menghitung jarak gabungan untuk setiap instance data sebagai jarak minimum untuk setiap referensi. Output widget dan instance data dengan jarak gabungan terendah.		Widget Neighbors menghitung tetangga terdekat untuk referensi yang diberikan dan untuk ukuran jarak tertentu. Referensi dapat berupa satu atau lebih instance. Dalam kasus dengan satu widget referensi, output terdekat n contoh dari data di mana n diatur oleh opsi Number of neighbors option pada widget. Ketika referensi mengandung lebih banyak instance widget menghitung jarak gabungan untuk setiap instance data sebagai jarak minimum untuk setiap referensi. Output widget dan instance data dengan jarak gabungan terendah.

	[[File:Neighbours-stamped.png\|center\|200px\|thumb]]		[[File:Neighbours-stamped.png\|center\|200px\|thumb]]

Onnowpurbo: /* Contoh */

2020-02-02T03:59:50Z

Contoh

← Older revision		Revision as of 03:59, 2 February 2020
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	[[File:Neighbours-example1.png\|center\|200px\|thumb]]		[[File:Neighbours-example1.png\|center\|200px\|thumb]]

	~~Now change the~~ selection Data Table to multiple examples. ~~As a result~~, ~~we get instances with closest combined distances to the references~~. ~~The method computes the combined distance as a~~ minimum ~~of distances to each reference~~.		Sekarang ubah selection Data Table menjadi multiple examples. Sebagai hasilnya, kita mendapatkan instance dengan jarak gabungan terdekat ke referensi. Metode ini menghitung jarak gabungan sebagai jarak minimum untuk setiap referensi.

	[[File:Neighbours-example-multiple.png\|center\|200px\|thumb]]		[[File:Neighbours-example-multiple.png\|center\|200px\|thumb]]

	~~Another example requires the installation of Image Analytics~~ add-on. ~~We loaded~~ 15 ~~paintings from famous painters with~~ Import Images widget ~~and passed them to~~ Image Embedding, ~~where we selected Painters embedder~~.		Contoh lain membutuhkan pemasangan add-on Image Analytics. Kita me-load 15 lukisan dari pelukis terkenal dengan Import Images widget dan menyerahkannya ke Image Embedding, dimana kita memilih Pelukis.

	~~Then the procedure is the same as above~~. ~~We passed~~ embedded images to Image Viewer ~~and selected a painting from~~ Monet ~~to serve as our reference image~~. ~~We passed the image to~~ Neighbors, ~~where we set the distance measure to cosine~~, ~~ticked off Exclude reference and set the neighbors to~~ 2. ~~This allows us to find the~~ actual closest neighbor ~~to a reference painting and observe them side by side in~~ Image Viewer (1).		Maka prosedurnya sama seperti di atas. Kita meneruskan embedded images ke Image Viewer dan memilih lukisan dari Monet untuk dijadikan gambar referensi kita. Kita meneruskan gambar ke Neighbors, tempat kami mengatur ukuran jarak ke cosinus, menandai agar exclude dari referensi dan menset ke neighbour ke 2. Ini memungkinkan kita untuk menemukan actual closest neighbor dengan lukisan referensi dan mengamati mereka berdampingan di Image Viewer (1).

	[[File:Neighbours-example2.png\|center\|200px\|thumb]]		[[File:Neighbours-example2.png\|center\|200px\|thumb]]

Onnowpurbo: /* Contoh */

2020-02-02T03:53:47Z

Contoh

← Older revision		Revision as of 03:53, 2 February 2020
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	==Contoh==		==Contoh==

	~~In the first example~~, ~~we used~~ iris ~~data and passed it to~~ Neighbors ~~and to~~ Data Table. In Data ~~Table~~, ~~we selected an instance of~~ iris, ~~that will serve as our reference~~, ~~meaning we wish to retrieve~~ 10 ~~closest examples to the select~~ data ~~instance~~. ~~We connect~~ Data Table to Neighbors ~~as well~~.		Pada contoh pertama, kita menggunakan data iris dan meneruskannya ke Neighbors dan Data Table. Dalam Tabel Data, kita memilih contoh iris, yang akan berfungsi sebagai referensi kita, artinya kita ingin mengambil 10 contoh terdekat ke instance data terpilih. Kita menghubungkan Data Table ke Neighbors juga.

	~~We can observe the results of~~ neighbor computation in Data Table (1), ~~where we can see~~ 10 ~~closest images to our selected~~ iris ~~flower~~.		Kita dapat mengamati hasil neighbor computation di Data Table (1), di mana kita dapat melihat 10 gambar terdekat dengan bunga iris pilihan kita.

	[[File:Neighbours-example1.png\|center\|200px\|thumb]]		[[File:Neighbours-example1.png\|center\|200px\|thumb]]
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	[[File:Neighbours-example2.png\|center\|200px\|thumb]]		[[File:Neighbours-example2.png\|center\|200px\|thumb]]



	==Referensi==		==Referensi==

Onnowpurbo at 03:31, 2 February 2020

2020-02-02T03:31:01Z

← Older revision		Revision as of 03:31, 2 February 2020
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	Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html		Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html

			Hitung tetangga terdekat dalam data sesuai dengan referensi.
	~~Compute nearest neighbors in~~ data ~~according to reference~~.

	==Input==		==Input==
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	Neighbors: A data table of nearest neighbors according to reference.		Neighbors: A data table of nearest neighbors according to reference.

	~~The~~ Neighbors widget ~~computes nearest neighbors for a given reference and for a given distance measure~~. ~~The reference can be either one~~ instance ~~or more instances~~. ~~In the case with one reference~~ widget ~~outputs closest~~ n ~~instances from~~ data ~~where~~ n ~~is set by the~~ Number of neighbors option ~~in the~~ widget. ~~When reference contains more instances~~ widget ~~computes the combined distance for each~~ data ~~instance as a~~ minimum ~~of distances to each reference~~. ~~Widget outputs n~~ data ~~instances with lowest combined distance~~.		Neighbors widget menghitung tetangga terdekat untuk referensi yang diberikan dan untuk ukuran jarak tertentu. Referensi dapat berupa satu atau lebih instance. Dalam kasus dengan satu widget referensi, output terdekat n contoh dari data di mana n diatur oleh opsi Number of neighbors option pada widget. Ketika referensi mengandung lebih banyak instance widget menghitung jarak gabungan untuk setiap instance data sebagai jarak minimum untuk setiap referensi. Output widget dan instance data dengan jarak gabungan terendah.

	[[File:Neighbours-stamped.png\|center\|200px\|thumb]]		[[File:Neighbours-stamped.png\|center\|200px\|thumb]]

Onnowpurbo at 01:20, 28 January 2020

2020-01-28T01:20:42Z

Onnowpurbo at 03:17, 22 January 2020

2020-01-22T03:17:55Z

← Older revision		Revision as of 03:17, 22 January 2020
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	Data: An input data set.		Data: An input data set.

	Reference: A reference data for neighbor computation.		Reference: A reference data for neighbor computation.

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	The Neighbors widget computes nearest neighbors for a given reference and for a given distance measure. The reference can be either one instance or more instances. In the case with one reference widget outputs closest n instances from data where n is set by the Number of neighbors option in the widget. When reference contains more instances widget computes the combined distance for each data instance as a minimum of distances to each reference. Widget outputs n data instances with lowest combined distance.		The Neighbors widget computes nearest neighbors for a given reference and for a given distance measure. The reference can be either one instance or more instances. In the case with one reference widget outputs closest n instances from data where n is set by the Number of neighbors option in the widget. When reference contains more instances widget computes the combined distance for each data instance as a minimum of distances to each reference. Widget outputs n data instances with lowest combined distance.

	~~../../_images/neighbours~~-stamped.png		[[File:Neighbours-stamped.png\|center\|200px\|thumb]]

	Distance measure for computing neighbors. Supported measures are: Euclidean, Manhattan, Mahalanobis, Cosine, Jaccard, Spearman, absolute Spearman, Pearson, absolute Pearson.		Distance measure for computing neighbors. Supported measures are: Euclidean, Manhattan, Mahalanobis, Cosine, Jaccard, Spearman, absolute Spearman, Pearson, absolute Pearson.

	Number of neighbors on the output.		Number of neighbors on the output.
			If Exclude rows (equal to) references is ticked, data instances that are highly similar to the Reference (distance < 1e-5), will be excluded.
	If Exclude rows (equal to) references is ticked, data instances that are highly similar to the ~~reference~~ (distance < 1e-5), will be excluded.

	Click Apply to commit the changes. To communicate changes automatically tick Apply Automatically.		Click Apply to commit the changes. To communicate changes automatically tick Apply Automatically.

	Status bar with access to widget help and information on the input and output data.		Status bar with access to widget help and information on the input and output data.

	~~Examples~~		==Contoh==

	In the first example, we used iris data and passed it to Neighbors and to Data Table. In Data Table, we selected an instance of iris, that will serve as our reference, meaning we wish to retrieve 10 closest examples to the select data instance. We connect Data Table to Neighbors as well.		In the first example, we used iris data and passed it to Neighbors and to Data Table. In Data Table, we selected an instance of iris, that will serve as our reference, meaning we wish to retrieve 10 closest examples to the select data instance. We connect Data Table to Neighbors as well.
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	We can observe the results of neighbor computation in Data Table (1), where we can see 10 closest images to our selected iris flower.		We can observe the results of neighbor computation in Data Table (1), where we can see 10 closest images to our selected iris flower.

	~~../../_images/neighbours~~-example1.png		[[File:Neighbours-example1.png\|center\|200px\|thumb]]

	Now change the selection Data Table to multiple examples. As a result, we get instances with closest combined distances to the references. The method computes the combined distance as a minimum of distances to each reference.		Now change the selection Data Table to multiple examples. As a result, we get instances with closest combined distances to the references. The method computes the combined distance as a minimum of distances to each reference.

	~~../../_images/neighbours~~-example-multiple.png		[[File:Neighbours-example-multiple.png\|center\|200px\|thumb]]

	Another example requires the installation of Image Analytics add-on. We loaded 15 paintings from famous painters with Import Images widget and passed them to Image Embedding, where we selected Painters embedder.		Another example requires the installation of Image Analytics add-on. We loaded 15 paintings from famous painters with Import Images widget and passed them to Image Embedding, where we selected Painters embedder.
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	Then the procedure is the same as above. We passed embedded images to Image Viewer and selected a painting from Monet to serve as our reference image. We passed the image to Neighbors, where we set the distance measure to cosine, ticked off Exclude reference and set the neighbors to 2. This allows us to find the actual closest neighbor to a reference painting and observe them side by side in Image Viewer (1).		Then the procedure is the same as above. We passed embedded images to Image Viewer and selected a painting from Monet to serve as our reference image. We passed the image to Neighbors, where we set the distance measure to cosine, ticked off Exclude reference and set the neighbors to 2. This allows us to find the actual closest neighbor to a reference painting and observe them side by side in Image Viewer (1).

	~~../../_images/neighbours~~-example2.png		[[File:Neighbours-example2.png\|center\|200px\|thumb]]

Onnowpurbo: Created page with "Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html Compute nearest neighbors in data according to reference. Inputs Data: An input data..."

2020-01-12T06:28:17Z

Created page with "Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html Compute nearest neighbors in data according to reference. Inputs Data: An input data..."

New page

Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html

Compute nearest neighbors in data according to reference.

Inputs

Data: An input data set.

Reference: A reference data for neighbor computation.

Outputs

Neighbors: A data table of nearest neighbors according to reference.

The Neighbors widget computes nearest neighbors for a given reference and for a given distance measure. The reference can be either one instance or more instances. In the case with one reference widget outputs closest n instances from data where n is set by the Number of neighbors option in the widget. When reference contains more instances widget computes the combined distance for each data instance as a minimum of distances to each reference. Widget outputs n data instances with lowest combined distance.

../../_images/neighbours-stamped.png

Distance measure for computing neighbors. Supported measures are: Euclidean, Manhattan, Mahalanobis, Cosine, Jaccard, Spearman, absolute Spearman, Pearson, absolute Pearson.

Number of neighbors on the output.

If Exclude rows (equal to) references is ticked, data instances that are highly similar to the reference (distance < 1e-5), will be excluded.

Click Apply to commit the changes. To communicate changes automatically tick Apply Automatically.

Status bar with access to widget help and information on the input and output data.

Examples

In the first example, we used iris data and passed it to Neighbors and to Data Table. In Data Table, we selected an instance of iris, that will serve as our reference, meaning we wish to retrieve 10 closest examples to the select data instance. We connect Data Table to Neighbors as well.

We can observe the results of neighbor computation in Data Table (1), where we can see 10 closest images to our selected iris flower.

../../_images/neighbours-example1.png

Now change the selection Data Table to multiple examples. As a result, we get instances with closest combined distances to the references. The method computes the combined distance as a minimum of distances to each reference.

../../_images/neighbours-example-multiple.png

Another example requires the installation of Image Analytics add-on. We loaded 15 paintings from famous painters with Import Images widget and passed them to Image Embedding, where we selected Painters embedder.

Then the procedure is the same as above. We passed embedded images to Image Viewer and selected a painting from Monet to serve as our reference image. We passed the image to Neighbors, where we set the distance measure to cosine, ticked off Exclude reference and set the neighbors to 2. This allows us to find the actual closest neighbor to a reference painting and observe them side by side in Image Viewer (1).

../../_images/neighbours-example2.png

==Referensi==

* https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html

==Pranala Menarik==

* [[Orange]]

← Older revision		Revision as of 01:20, 28 January 2020
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	Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html		Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/neighbors.html



	Compute nearest neighbors in data according to reference.		Compute nearest neighbors in data according to reference.

	~~Inputs~~		==Input==

	Data: An input data set.		Data: An input data set.
	Reference: A reference data for neighbor computation.		Reference: A reference data for neighbor computation.

	~~Outputs~~		==Output==

	Neighbors: A data table of nearest neighbors according to reference.		Neighbors: A data table of nearest neighbors according to reference.

	The Neighbors widget computes nearest neighbors for a given reference and for a given distance measure. The reference can be either one instance or more instances. In the case with one reference widget outputs closest n instances from data where n is set by the Number of neighbors option in the widget. When reference contains more instances widget computes the combined distance for each data instance as a minimum of distances to each reference. Widget outputs n data instances with lowest combined distance.		The Neighbors widget computes nearest neighbors for a given reference and for a given distance measure. The reference can be either one instance or more instances. In the case with one reference widget outputs closest n instances from data where n is set by the Number of neighbors option in the widget. When reference contains more instances widget computes the combined distance for each data instance as a minimum of distances to each reference. Widget outputs n data instances with lowest combined distance.
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	[[File:Neighbours-stamped.png\|center\|200px\|thumb]]		[[File:Neighbours-stamped.png\|center\|200px\|thumb]]

	Distance measure for computing neighbors. Supported measures are: Euclidean, Manhattan, Mahalanobis, Cosine, Jaccard, Spearman, absolute Spearman, Pearson, absolute Pearson.		* Distance measure for computing neighbors. Supported measures are: Euclidean, Manhattan, Mahalanobis, Cosine, Jaccard, Spearman, absolute Spearman, Pearson, absolute Pearson.
	Number of neighbors on the output.		* Number of neighbors on the output.
	If Exclude rows (equal to) references is ticked, data instances that are highly similar to the Reference (distance < 1e-5), will be excluded.		* If Exclude rows (equal to) references is ticked, data instances that are highly similar to the Reference (distance < 1e-5), will be excluded.
	Click Apply to commit the changes. To communicate changes automatically tick Apply Automatically.		* Click Apply to commit the changes. To communicate changes automatically tick Apply Automatically.
	Status bar with access to widget help and information on the input and output data.		* Status bar with access to widget help and information on the input and output data.

	==Contoh==		==Contoh==