Closed amukh18 closed 3 years ago
@amukh18 Can I work on this issue? But I have already have put a pull request for #28 issue
@RohanSahana you may work on this issue. This issue and issue #28 are different issues. This is a classification problem.
As per note, I request @amukh18 to review my pull request. The code has been modified as per your request (https://github.com/WebClub-NITK/Hacktoberfest-2k20/pull/57#issuecomment-706130303) and (https://github.com/WebClub-NITK/Hacktoberfest-2k20/pull/57#issuecomment-705471159).
@RohanSahana I have reviewed your PR. The changes are correct. Good job on your PR!
Description
Given the characteristics of the cell nuclei present in the image of a fine needle aspirate (FNA) of a breast mass, predict if the breast cancer tumour is malignant or benign.
The dataset contains one id column, 30 real valued feature columns, and one string column. Ten real-valued features are computed for each cell nucleus:
a) radius (mean of distances from center to points on the perimeter) b) texture (standard deviation of gray-scale values) c) perimeter d) area e) smoothness (local variation in radius lengths) f) compactness (perimeter^2 / area - 1.0) g) concavity (severity of concave portions of the contour) h) concave points (number of concave portions of the contour) i) symmetry j) fractal dimension ("coastline approximation" - 1)
The mean, standard error and "worst" or largest (mean of the three largest values) of these features were computed for each image, resulting in 30 features. For instance, field 3 is Mean Radius, field 13 is Radius SE, field 23 is Worst Radius.
You may import the dataset using the following code:
You may also obtain the dataset from the following link: UCI Machine Learning repository
Output: 'M' for malignant, 'B' for benign.
Details
Issue requirements / progress
Resources
scikit-learn logistic regression documentation: scikit-learn random forest classifier documentation: scikit-learn support vector machine documentation:
Directory Structure
Create a directory named
breast_cancer_prediction
. Inside it, create the following directories:logreg
for the logistic regression modelrandom_forest
for the random forest modelsvm
for the support vector machine model Put your file for each model in the respective directory.Note