Project Description

This project (Implementing binary classification of lung cancer using supervised machine learning)is about the implementation of binary classification of lung cancer using supervised learning. Repositories such as UCI contains many dataset such as lung cancer, iris dataset, heart disease which can be downloaded from here. In this project, if you look at the dataset, target is binary hence support vector classification, logistic regression, KNN, Naive bayes. Please read more about it from section1.4)What does this document contains:

1.1)Topic Headline

Implementing binary classification of lung cancer using supervised machine learning

1.2) Hardware requirement:

For Matlab 2017a

Intel processor x86-64 processor (64 bit), 6 GB hard disk, 2-4 GB RAM. For simulink 4 GB is required.

For Matlab 2015a

Processor x86-64 processor (32 bit or 64 bit), 4 GB hard disk, 2 GB RAM. If RAM is more it is good.

Note

If your window is 32 bit 64 bit will not get installed so consider this point before installing. R2015b is the last release of the 32-bit version of MATLAB for Windows. Math-Works releases subsequent to R2015b will not be available for the 32-bit Windows operating system

1.3) Language Used

Matlab is the language used. Matlab files are saved with .m extension.

1.4) What does this document contains:

Machine Learning is used for various purpose such as color based segmentation, predicting diseases, image processing applications such as object detection, image classification and transfer learning. When deep learning came the computation power has improved to such level that now it is possible for the machines to work like humans. Companies like Interest, Google, Facebook and Amazon is using this technology to so large extent that their revenues have increased dramatically. In this thesis we have tried to use support vector machine model to implement binary classification of lung cancer using supervised machine learning.

1.4.1) Dataset Taken

Data is taken from UCI Machine learning Repository. I have downloaded the data and provide you the direct link to download the data. Please visit this link and download the data https://drive.google.com/open?id=1au8e1ZOMdjBXKQ9Dj_-BqNG4ReYNf1nd

Data and Target are created

Pre-processing is done and data is cleaned

Data is imported in MATLAB

1.4.2) Flowchart to demonstrate how work has been implemented

Implementing binary classification of lung cancer using supervised machine learning Workflow
Binary classification of lung cancer using supervised machine learning Workflow

1.4.3) How to run the code

MATLAB environment is used to run this code. You must have MATLAB installed in your system. If not please install the Matlab and keep these files function_importing.m, lung-cancer.data and main_function.m in a folder and run main_function.m.