wanjohiwanjohi / breast_cancer-exploration Goto Github PK

The repository contains a brief introductory project to classification method of machine learning and makes use of the following models:

• Naive Bayes (GaussianNaiveBayes from sklearn.classification)
• Logistic Regression (LogisticRegression from sklearn.linear)

The data used herein is found as part of the sklearn datasets and contains attributes such as:

radius (mean of distances from center to points on the perimeter)

texture (standard deviation of gray-scale values)

perimeter

area

smoothness (local variation in radius lengths)

compactness (perimeter^2 / area - 1.0)

concavity (severity of concave portions of the contour)

concave points (number of concave portions of the contour)

symmetry

fractal dimension (“coastline approximation” - 1)

Using the features provided , predict the class of breast cancer ; whether malignant or benign

The model performance metric used is the accuracy