Download complete DMBI Practical solutions (ARM, Naive Bayes, Decision Tree, K-Means, Hierarchical Clustering) to your working directory.
Project description
dmbi-downloader
A pip-installable package that downloads the complete DMBI Practical All Solutions Python file directly to your working directory with a single function call.
📦 Installation
pip install dmbi-downloader
Or install locally from source:
pip install .
🚀 Usage
Option 1 – Python import (recommended)
from dmbi_downloader import download
download()
# ✅ Saved to: /your/current/folder/DMBI_Practical_All_Solutions.txt
Option 2 – Custom filename
from dmbi_downloader import download
download("my_dmbi_code.txt")
Option 3 – Run as module
python -m dmbi_downloader
Option 4 – Console command (after pip install)
dmbi-download
📁 What gets downloaded?
A single .txt file named DMBI_Practical_All_Solutions.txt containing complete Python code for:
| # | Topic | Questions |
|---|---|---|
| 1 | Association Rule Mining – Apriori (Real Datasets) | Q1–Q10 |
| 2 | Association Rule Mining – Apriori (Custom Datasets) | Q1–Q10 |
| 3 | Naive Bayes Classifier (Real Datasets) | Q1–Q10 |
| 4 | Naive Bayes Classifier (Custom Datasets) | Q1–Q10 |
| 5 | Decision Tree Classifier (Real Datasets) | Q1–Q10 |
| 6 | Decision Tree Classifier (Custom Datasets) | Q1–Q10 |
| 7 | K-Means Clustering (Real Datasets) | Q1–Q10 |
| 8 | K-Means Clustering (Custom Datasets) | Q1–Q10 |
| 9 | Hierarchical Clustering (Real Datasets) | Q1–Q10 |
| 10 | Hierarchical Clustering (Custom Datasets) | Q11–Q20 |
🔧 Requirements to run the downloaded code
pip install pandas numpy matplotlib seaborn scikit-learn mlxtend
📄 License
MIT
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