Skip to content

Latest commit

 

History

History
15 lines (11 loc) · 558 Bytes

README.md

File metadata and controls

15 lines (11 loc) · 558 Bytes

ML_With_Python

"The best classifier" assignment from Machine Learning with Python course by IBM in Coursera

Loads a historical dataset from previous loan applications, cleans the data, and applies different classification algorithm on the data. The following algorithms are used to build the models:

k-Nearest Neighbour
Decision Tree
Support Vector Machine
Logistic Regression

The results are reported as the accuracy of each classifier, using the following metrics when these are applicable:

Jaccard index
F1-score
LogLoss