Difference between revisions of "Orange: Naive Bayes"

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[[File:NaiveBayes-stamped.png|center|200px|thumb]]
 
[[File:NaiveBayes-stamped.png|center|200px|thumb]]
  
This widget has two options: the name under which it will appear in other widgets and producing a report. The default name is Naive Bayes. When you change it, you need to press Apply.
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Widget ini memiliki dua opsi: nama yang akan ditampilkan di widget lain dan menghasilkan report. Nama standarnya adalah Naive Bayes. Ketika kita mengubahnya, kita perlu menekan Apply.
  
 
==Contoh==
 
==Contoh==

Revision as of 15:31, 6 March 2020

Sumber: https://docs.biolab.si//3/visual-programming/widgets/model/naivebayes.html


Klasifikasi probabilistik yang cepat dan sederhana berdasarkan teorema Bayes dengan asumsi independensi feature.

Input

Data: input dataset
Preprocessor: preprocessing method(s)

Output

Learner: naive bayes learning algorithm
Model: trained model

Widget Naive Bayes mempelajari model Naive Bayesian dari data. Widget ini hanya berfungsi untuk task classification.

NaiveBayes-stamped.png

Widget ini memiliki dua opsi: nama yang akan ditampilkan di widget lain dan menghasilkan report. Nama standarnya adalah Naive Bayes. Ketika kita mengubahnya, kita perlu menekan Apply.

Contoh

Here, we present two uses of this widget. First, we compare the results of the Naive Bayes with another model, the Random Forest. We connect iris data from File to Test & Score. We also connect Naive Bayes and Random Forest to Test & Score and observe their prediction scores.

NaiveBayes-classification.png

The second schema shows the quality of predictions made with Naive Bayes. We feed the Test & Score widget a Naive Bayes learner and then send the data to the Confusion Matrix. We also connect Scatter Plot with File. Then we select the misclassified instances in the Confusion Matrix and show feed them to Scatter Plot. The bold dots in the scatterplot are the misclassified instances from Naive Bayes.

NaiveBayes-visualize.png

Referensi

Pranala Menarik