- Notifications
You must be signed in to change notification settings - Fork0
The data set obtained from Kaggle athttps://www.kaggle.com/uciml/breast-cancer-wisconsin-data/data. This repository demonstrates some basic data analysis operations to be performed in python using numpy, patplotlib and pandas.
sickRanchez-c137/BreastCancerDataAnalysis
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
The data set obtained from Kaggle athttps://www.kaggle.com/uciml/breast-cancer-wisconsin-data/data. This repository demonstrates some basic data analysis operations to be performed in python using numpy, patplotlib and pandas.
The jupyter notebook file can be found atpynb file.
Following table shows the different classification techniques used.
| Classification Method |
|---|
| Random Forest (Gini) |
| Random Forest (Entropy) |
| Multi Layer Perception (ReLU) |
| Multi Layer Perception (tanh) |
| Multi Layer Perception (sigmoid) |
| SVM NuSVC |
| SVM LinearSVC |
| SVM SVC Linear |
| SVM SVC RBF |
| Gaussian Naive Bayes |
| Decision Tree (Gini) |
| Decision Tree (Entropy) |
| Logistic Regression |
| KNN |
After analyzing the accuracy of all the models, the conclusion reached are:
- KNN with p=2 and num of neighbour at 5% of total data sets gives 98.2% accuracy
- Multi Layer Perceptron with tanh activation with 12 hidden layers gives 98.2% accuracy on Validation Set
About
The data set obtained from Kaggle athttps://www.kaggle.com/uciml/breast-cancer-wisconsin-data/data. This repository demonstrates some basic data analysis operations to be performed in python using numpy, patplotlib and pandas.
Topics
Resources
Uh oh!
There was an error while loading.Please reload this page.