https://github.com/jeffreywijaya100/boston-datamining
Using Boston dataset in Rstudio to train predictive models using logistic regression and decision trees and evaluate the performance of those models.
https://github.com/jeffreywijaya100/boston-datamining
boston boston-housing-dataset data-mining datamining r rstudio
Last synced: 7 months ago
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Using Boston dataset in Rstudio to train predictive models using logistic regression and decision trees and evaluate the performance of those models.
- Host: GitHub
- URL: https://github.com/jeffreywijaya100/boston-datamining
- Owner: jeffreywijaya100
- Created: 2024-10-14T13:10:44.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-12T15:19:51.000Z (11 months ago)
- Last Synced: 2025-01-23T21:17:44.239Z (9 months ago)
- Topics: boston, boston-housing-dataset, data-mining, datamining, r, rstudio
- Homepage:
- Size: 599 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
Train predictive models using logistic regression and decision trees and evaluate the performance of those models. You have to decide which model you choose.
The dataset coming from the library(MASS)
data(Boston)
Originally, this dataset is for Regression tasks. However, you should perform classification for the assignment by following this condition.
Transform the label(target variable) which is 'medv' into 2 class where
medv <= 21 --> low
medv >21 --> high