Orange: Correspondence Analysis - Revision history

Onnowpurbo: /* Contoh */

2020-02-22T22:45:40Z

Contoh

Onnowpurbo at 22:00, 22 February 2020

2020-02-22T22:00:45Z

Onnowpurbo at 01:07, 29 January 2020

2020-01-29T01:07:02Z

Onnowpurbo at 00:42, 24 January 2020

2020-01-24T00:42:09Z

Onnowpurbo: Created page with "Sumber: https://docs.biolab.si//3/visual-programming/widgets/unsupervised/correspondenceanalysis.html Correspondence analysis for categorical multivariate data. Inputs..."

2020-01-16T23:51:29Z

Created page with "Sumber: https://docs.biolab.si//3/visual-programming/widgets/unsupervised/correspondenceanalysis.html Correspondence analysis for categorical multivariate data. Inputs..."

New page

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

Correspondence analysis for categorical multivariate data.

Inputs

Data: input dataset

Outputs

Coordinates: coordinates of all components

Correspondence Analysis (CA) computes the CA linear transformation of the input data. While it is similar to PCA, CA computes linear transformation on discrete rather than on continuous data.

../../_images/CorrespondenceAnalysis-stamped.png

Select the variables you want to see plotted.

Select the component for each axis.

Inertia values (percentage of independence from transformation, i.e. variables are in the same dimension).

Produce a report.

Example

Below, is a simple comparison between the Correspondence Analysis and Scatter Plot widgets on the Titanic dataset. While the Scatter Plot shows fairly well which class and sex had a good survival rate and which one didn’t, Correspondence Analysis can plot several variables in a 2-D graph, thus making it easy to see the relations between variable values. It is clear from the graph that “no”, “male” and “crew” are related to each other. The same goes for “yes”, “female” and “first”.

../../_images/CorrespondenceAnalysis-Example.png

==Referensi==

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

==Pranala Menarik==

* [[Orange]]

← Older revision		Revision as of 22:45, 22 February 2020
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−		+	'''WARNING:''' Scatter Plot yang baru tidak bisa untuk diskrit data. Scatter Plot yang baru hanya untuk data kontinyu.

	==Referensi==		==Referensi==

@@ Line 2: / Line 2: @@
-Correspondence analysis for categorical multivariate data.
+Correspondence analysis untuk categorical multivariate data.
 ==Input==
@@ Line 12: / Line 12: @@
   Coordinates: coordinates of all components
-Correspondence Analysis (CA) computes the CA linear transformation of the input data. While it is similar to PCA, CA computes linear transformation on discrete rather than on continuous data.
+Correspondence Analysis (CA) menghitung transformasi linear CA dari data input. Meskipun mirip dengan PCA, CA menghitung transformasi linear pada data diskrit bukan pada data kontinu.
 [[File:CorrespondenceAnalysis-stamped.png|center|200px|thumb]]
 * Select the variables you want to see plotted.
@@ Line 24: / Line 23: @@
 ==Contoh==
-Below, is a simple comparison between the Correspondence Analysis and Scatter Plot widgets on the Titanic dataset. While the Scatter Plot shows fairly well which class and sex had a good survival rate and which one didn’t, Correspondence Analysis can plot several variables in a 2-D graph, thus making it easy to see the relations between variable values. It is clear from the graph that “no”, “male” and “crew” are related to each other. The same goes for “yes”, “female” and “first”.
+Di bawah, adalah perbandingan sederhana antara widget Correspondence Analysis dan Scatter Plot pada dataset Titanic. Sementara Scatter Plot menunjukkan dengan cukup baik kelas dan jenis kelamin mana yang memiliki tingkat kelangsungan hidup yang baik dan mana yang tidak, Correspondence Analysis dapat memplot beberapa variabel dalam grafik 2-D, sehingga memudahkan untuk melihat hubungan antara nilai-nilai variabel. Jelas dari grafik bahwa  “no”, “male” dan “crew”  terkait satu sama lain. Hal yang sama berlaku untuk “yes”, “female” dan “first”.
 [[File:CorrespondenceAnalysis-Example.png|center|200px|thumb]]

@@ Line 4: / Line 4: @@
 Correspondence analysis for categorical multivariate data.
-Inputs
+==Input==
-    Data: input dataset
+ Data: input dataset
-Outputs
+==Output==
-    Coordinates: coordinates of all components
+ Coordinates: coordinates of all components
 Correspondence Analysis (CA) computes the CA linear transformation of the input data. While it is similar to PCA, CA computes linear transformation on discrete rather than on continuous data.
@@ Line 17: / Line 17: @@
-    Select the variables you want to see plotted.
+* Select the variables you want to see plotted.
-    Select the component for each axis.
+* Select the component for each axis.
-    Inertia values (percentage of independence from transformation, i.e. variables are in the same dimension).
+* Inertia values (percentage of independence from transformation, i.e. variables are in the same dimension).
-    Produce a report.
+* Produce a report.
 ==Contoh==