Breast Cancer Prediction

Breast Cancer Prediction Using Machine Learning Algorithms

Objective:

• To study the dataset available on breast cancer and predict the results to use it for predictions.
• To do an exploratory data analysis on the data
• Create an ML-model & do a comparative analysis of all the models to conclude to our best ML-model for prediction of breast cancer

Importing packages & lib-dependencies:

• import warnings
• import numpy
• import pandas
• import matplotlib.pyplot (for visualization of data)
• import seaborn
• import sklearn.model (all ml-algorithms are available in this library)

Data set:

• Dataset for this project is available on this kaggle as Breast Cancer Wisconsin (Diagnostic) Data Set

ML-Model:

• Fitting in ML -> process of storing required data and predicting the result is called fitting in machine learning
• Independent variable : a variable which is not dependable on other entity.
• Dependent variable : a variable which is dependable on other entity.
• Train-test split model is used for ML model to train machine for required dataset and testing the machine for prediction results inorder to reach to our best model conclusion.

Anaconda Navigator:

• It is an GUI for desktop which allows to launch applications and easily manage conda packages.
• It provides with an environment and channel for programming without launchng command line.
• It contains coding applications like spyder orange,jupyter lab,jupyter notebook,glue,visual studio code etc.

Jupyter Notebbok:

• Open web source application that allows to create & share documents that contain live code ,equations,visualizations and narrative texts.
• It uses extensions as .pynb where py stands for python.
• It is used to write codes as it allows more clear and neat visualization of python coding.
• It is a web based interface so it opens in browser but doesnt require internet connectivity.

Jovian:

• It is a platform for sharing and collaborating an jupyter notebooks and data-science projects.

Open a project folder through command line:

• Select a particular folder in OS and copy the location of folder where you wish to create ML-project
• Open windows and click on Anaconda prompt
• Type cd ==> cd stands for change directory and paste the location path of project folder
• add the directory initial followed by colon
• your project folder will open up in notebook