GitHub / abdoghareeb46 / NTI-Final-Assignment
NTI-Final-Assignment Use flask(python) and shiny dashboard (R) to build simple user interface to see how choosing classification model may affect prediction accuracy, using Customer Churn Dataset.
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PURL: pkg:github/abdoghareeb46/NTI-Final-Assignment
Stars: 2
Forks: 0
Open issues: 0
License: None
Language: Jupyter Notebook
Size: 534 KB
Dependencies parsed at: Pending
Created at: over 6 years ago
Updated at: over 1 year ago
Pushed at: over 6 years ago
Last synced at: over 1 year ago
Topics: classification-algorithims, data-analysis, data-science, flask-api, imbalanced-data, jupyter-notebook, machine-learning, machine-learning-algorithms, oversampling, prediction-algorithm, python, r, randomoversampler, shinydashboard, smote