https://github.com/arnabd64/classifier-comparison-1
https://github.com/arnabd64/classifier-comparison-1
bayes-classifier binary-classification knn-classification logistic-regression random-forest-classifier scikit-learn svm-classifier
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/arnabd64/classifier-comparison-1
- Owner: arnabd64
- Archived: true
- Created: 2021-06-20T06:29:53.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-06-21T06:02:01.000Z (almost 5 years ago)
- Last Synced: 2025-03-04T17:50:31.808Z (over 1 year ago)
- Topics: bayes-classifier, binary-classification, knn-classification, logistic-regression, random-forest-classifier, scikit-learn, svm-classifier
- Language: Jupyter Notebook
- Homepage:
- Size: 758 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# Comparing Binary Classification Models
## Instructions
- To view the notebook, please click `notebook.ipynb` in the above section.
- To see the Python script, click on `script.py`.
- To download the dataset using Browser, click on `SUV_Purchase` --> Right Click on `Raw` --> Click on `Save Link As`.
- To import this dataset in python, use:
```python
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/arnabd64/classifier-comparison-1/main/SUV_Purchase.csv')
```
- To import this dataset in R, use:
```r
df <- read.csv('https://raw.githubusercontent.com/arnabd64/classifier-comparison-1/main/SUV_Purchase.csv')
```
## About notebook
The aim of this notebook is to provide a simple comparison between several classification models. The models included are:
1. Logistic Regression
2. k-Nearest Neighbors
3. Decision Tree Classifier
4. Random Forest Classifier
5. Naive Bayes Classifier
6. Support Vector Machines
## About me
- [LinkedIn](https://github.com/arnabd64/resume/blob/main/linkedin.com/in/arnab-dhar)
- [GitHub](https://github.com/arnabd64)
- [Resume on GitHub](https://github.com/arnabd64/resume)