diabetes_data_upload

Citation Author(s):
Chao-Yu
Guo
Naitional Yang Ming Chiao Tung University
Yi-Jyun
Lin
Submitted by:
Chao-Yu Guo
Last updated:
Wed, 01/04/2023 - 07:11
DOI:
10.21227/8mrc-z624
Data Format:
*.avi; *.csv; *.txt
Research Article Link:
Random Interaction Forest (RIF) – A Novel Machine Learning Strategy Accounting for Feature Interaction
License:
Creative Commons Attribution
880 Views
Categories:
Artificial Intelligence
Keywords:
Early Stage Diabetes Risk Prediction Dataset, University of California, Irvine (UCI) machine learning Repository
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Abstract 

"Early Stage Diabetes Risk Prediction Dataset" from the University of California, Irvine (UCI) machine learning Repository. This data was collected from a direct questionnaire of patients from the Diabetes Hospital in Sylhet, Bangladesh. It contains a total of 520 people with diabetes. Related symptoms are in the reference, of which 320 people have diabetes, and 200 do not.

Instructions: 

The R code of the Random Interaction Forest use this dataset as an application.

## Step 1: Change the directory and data set name

data = read.csv("Path_To_diabetes_data_upload/diabetes_data_upload.csv", header = T)

## Step 2:Define the number of variables selected in random forrest

Comments

The first version of R code that implements the Random Interaction Forest (RIF)

Submitted by Chao-Yu Guo on Wed, 01/04/2023 - 07:13

Thanks

Submitted by Giovanni E Gonzalez on Wed, 04/19/2023 - 14:01

Thanks

Submitted by Soha Aldossary on Wed, 03/27/2024 - 16:02

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