Class Imbalance and Classification Metrics With Aircraft Wildlife Strikes
Offered By: Julia Silge via YouTube
Course Description
Overview
Explore how handling class imbalance in modeling affects different classification metrics using a dataset on predicting damage from aircraft strikes with wildlife. Learn about data overview, exploratory data analysis, model building, cross-validation, sensitivity, preprocessing, and imbalance workflow. Discover techniques like numeric variable analysis, pears plot, bagtree modeling, and balancing results to improve classification performance.
Syllabus
Introduction
Data
Test Data
Data Overview
numeric variables
exploratory data analysis
pears plot
build model
crossvalidation
sensitivity
preprocessing
modeling
unknown
bagtree
imbalance workflow
cross validation
sensitivity and specificity
balanced result
conclusion
Taught by
Julia Silge
Related Courses
80043368 - Strategies to Improve Human Papillomavirus (HPV) Vaccination Rates Among College StudentsJohns Hopkins University via Independent MBA Core Curriculum
University System of Maryland via edX A Beginner’s Guide to Data Analytics
Boxplay via FutureLearn A Beginner’s Guide to Data Handling and Management in Excel
Packt via FutureLearn A Day in the Life of a Data Engineer (Korean)
Amazon Web Services via AWS Skill Builder