Orange: Feature Ranking - Revision history

Onnowpurbo at 09:21, 11 February 2025

2025-02-11T09:21:00Z

Onnowpurbo at 01:13, 15 March 2022

2022-03-15T01:13:24Z

Onnowpurbo at 23:02, 20 April 2020

2020-04-20T23:02:28Z

Onnowpurbo at 20:56, 27 January 2020

2020-01-27T20:56:16Z

Onnowpurbo at 20:55, 27 January 2020

2020-01-27T20:55:39Z

Onnowpurbo at 00:26, 8 January 2020

2020-01-08T00:26:41Z

Onnowpurbo: Created page with "Sumber:https://orange.biolab.si/workflows/ For supervised problems, where data instances are annotated with class labels, we would like to know which are the most informativ..."

2020-01-08T00:23:34Z

Created page with "Sumber:https://orange.biolab.si/workflows/ For supervised problems, where data instances are annotated with class labels, we would like to know which are the most informativ..."

New page

Sumber:https://orange.biolab.si/workflows/

For supervised problems, where data instances are annotated with class labels, we would like to know which are the most informative features. Rank widget provides a table of features and their informativity scores, and supports manual feature selection. In the workflow, we used it to find the best two features (of initial 79 from brown-selected dataset) and display its scatter plot.

[[File:Feature-ranking.png|center|400px|thumb]]

==Source==

* https://service.biolab.si/download/workflow?name=410-feature-ranking.ows&domain=orange

==Referensi==

* https://orange.biolab.si/workflows/

==Pranala Menarik==

* [[Orange]]

← Older revision		Revision as of 09:21, 11 February 2025
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	[[File:Feature-ranking.png\|center\|400px\|thumb]]		[[File:Feature-ranking.png\|center\|400px\|thumb]]
		+
		+
		+
		+	The image represents an '''Orange Data Mining workflow '''designed for''' data preprocessing, feature selection, and visualization'''.
		+
		+	=='''Workflow Breakdown:'''==
		+
		+	1. '''File (Data Input)'''
		+	* Loads a dataset that may contain missing values and multiple features.
		+
		+	2. '''Impute (Handling Missing Values)'''
		+	* This step '''fills in missing values''' to ensure that all data points are available for further processing.
		+	* The note mentions that imputation was necessary for proper visualization.
		+
		+	3. '''Rank (Feature Selection)'''
		+	* This widget '''evaluates feature importance''' and ranks them based on their relevance.
		+	* The two most informative features were selected for further analysis.
		+
		+	4. '''Scatter Plot (Visualization)'''
		+	* The selected features are used to generate a '''scatter plot'''.
		+	* The note suggests checking whether the '''most informative features''' provide a '''good class separation''' in the data.
		+
		+	=='''Purpose of the Workflow:'''==
		+	* '''Handles missing values''' through imputation.
		+	* '''Ranks features''' based on informativeness to select the best predictors.
		+	* '''Visualizes''' the most relevant features using a '''scatter plot''' to assess data separability.
		+
		+	This workflow is '''useful for feature engineering and exploratory data analysis''', helping in selecting the best attributes for machine learning models.
		+

	==Source==		==Source==

← Older revision		Revision as of 23:02, 20 April 2020
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−	Untuk masalah yang supervised, di mana instance data dijelaskan dengan class label, kita ingin tahu feature mana yang paling informatif. Rank ~~Widget~~ menyediakan tabel fitur dan skor informativitasnya, dan mendukung pemilihan fitur manual. Dalam workflow, kita menggunakannya untuk menemukan dua fitur terbaik (dari 79 awal dari dataset yang dipilih) dan menampilkan ~~scatter plot-nya~~.	+	Untuk masalah yang supervised, di mana instance data dijelaskan dengan class label, kita ingin tahu feature mana yang paling informatif. Widget Rank menyediakan tabel fitur dan skor informativitasnya, dan mendukung pemilihan fitur manual. Dalam workflow, kita menggunakannya untuk menemukan dua fitur terbaik (dari 79 awal dari dataset yang dipilih) dan menampilkan di widget Scatter Plot.

	[[File:Feature-ranking.png\|center\|400px\|thumb]]		[[File:Feature-ranking.png\|center\|400px\|thumb]]

← Older revision		Revision as of 20:56, 27 January 2020
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	* YOUTUBE: https://www.youtube.com/watch?v=p5XLWmSUxTQ		* YOUTUBE: https://www.youtube.com/watch?v=p5XLWmSUxTQ
		+	* YOUTUBE: https://www.youtube.com/watch?v=Fw5SztV5p3E
	* https://orange.biolab.si/workflows/		* https://orange.biolab.si/workflows/

@@ Line 2: / Line 2: @@
-Untuk masalah yang supervised, di mana instance data dijelaskan dengan class label, kita ingin tahu fitur mana yang paling informatif. Rank Widget menyediakan tabel fitur dan skor informativitasnya, dan mendukung pemilihan fitur manual. Dalam workflow, kita menggunakannya untuk menemukan dua fitur terbaik (dari 79 awal dari dataset yang dipilih) dan menampilkan scatter plot-nya.
+Untuk masalah yang supervised, di mana instance data dijelaskan dengan class label, kita ingin tahu feature mana yang paling informatif. Rank Widget menyediakan tabel fitur dan skor informativitasnya, dan mendukung pemilihan fitur manual. Dalam workflow, kita menggunakannya untuk menemukan dua fitur terbaik (dari 79 awal dari dataset yang dipilih) dan menampilkan scatter plot-nya.
 [[File:Feature-ranking.png|center|400px|thumb]]
@@ Line 12: / Line 12: @@
 ==Referensi==
 * https://orange.biolab.si/workflows/

← Older revision		Revision as of 00:26, 8 January 2020
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−	~~For~~ supervised ~~problems~~, ~~where~~ data ~~instances are annotated with~~ class ~~labels~~, ~~we would like to know which are the most informative features~~. Rank ~~widget provides a table of features and their informativity scores~~, ~~and supports~~ manual ~~feature selection~~. ~~In the~~ workflow, ~~we used it to find the best two features~~ (~~of initial~~ 79 ~~from brown-selected~~ dataset) ~~and display its~~ scatter plot.	+	Untuk masalah yang supervised, di mana instance data dijelaskan dengan class label, kita ingin tahu fitur mana yang paling informatif. Rank Widget menyediakan tabel fitur dan skor informativitasnya, dan mendukung pemilihan fitur manual. Dalam workflow, kita menggunakannya untuk menemukan dua fitur terbaik (dari 79 awal dari dataset yang dipilih) dan menampilkan scatter plot-nya.

	[[File:Feature-ranking.png\|center\|400px\|thumb]]		[[File:Feature-ranking.png\|center\|400px\|thumb]]

@@ Line 8: / Line 8: @@
 ==Source==
-* https://service.biolab.si/download/workflow?name=410-feature-ranking.ows&domain=orange
+* https://orangedatamining.com/workflows/Feature-Ranking/
 ==Referensi==