https://github.com/robi56/ml_project_template
Building a machine learning project named Breast Cancer Classification using Python 3.6, IPython Notebook and Python Virtual Environment
https://github.com/robi56/ml_project_template
cancer-research deep-learning machine-learning python3
Last synced: 8 months ago
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Building a machine learning project named Breast Cancer Classification using Python 3.6, IPython Notebook and Python Virtual Environment
- Host: GitHub
- URL: https://github.com/robi56/ml_project_template
- Owner: robi56
- License: mit
- Created: 2018-03-30T06:42:54.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-06-06T06:20:38.000Z (over 7 years ago)
- Last Synced: 2025-01-04T03:14:28.754Z (9 months ago)
- Topics: cancer-research, deep-learning, machine-learning, python3
- Language: Python
- Homepage:
- Size: 67.4 KB
- Stars: 3
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# ML_Project_Template
Building a machine learning project using IPython Notebook and Python Virtual Environment
## Install Jupiter NoteBook
```
pip3 install --upgrade pip
pip3 install jupyter
```
## Pip3 Installation Problem Solution
https://stackoverflow.com/questions/49836676/python-pip3-cannot-import-name-main-error-after-upgrading-pip?utm_medium=organic&utm_source=google_rich_qa&utm_campaign=google_rich_qa
## Setting Python RunTime via virtual environment
Step 1: Go go the project directory , then 1) create a directory for virtual enviroment , add python libary to be installed to the requirements.txt file and then install all the requirements
```
mkdir project_dependencies
virtualenv -p /usr/local/bin/python3.6 project_dependencies/
source project_dependencies/bin/activate
nano requirements.txt
pip install -r requirements.txt
```
Step 2: Select the kernal depedency from virtual environment
```
pip install ipykernel
ipython kernel install --user --name=project_dependencies
```
Step 3: Run the jupiter Notebook by the follwing command
```
jupyter notebook
```
## Experiment
### Data Collection:
Data is collected from http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data
### Methods
Deep Learning - Recurrent Neural Network
Machine Learning - Decision Tree, Support Vector Machine, GradientBoosting
### Run
- Go the models/machine_learning/decision_tree
- Run the main.py file
- Result will be saved in results folder
### Result
Every Run of a script gives a new result file which contains the information like below
```
{
"accuracy": 0.9649122807017544,
"confusion_matrix": [
[
134,
4
],
[
4,
86
]
],
"hyper_parameters": {
"learning_rate": 0.1
},
"labels": [
"Malignant",
"benign"
],
"precision": 0.9306302794022092,
"recall": 0.9555555555555556
}
```