Application of Classification Algorithms

Explore the application of classification algorithms in this comprehensive video lecture. Dive into comparisons between popular classification techniques, examining factors that influence their performance. Learn to evaluate algorithm effectiveness through a real-world case study on employee promotion prediction. Begin with an introduction to classification concepts, then progress through data preprocessing, logistic regression, support vector machines, k-nearest neighbors, Naive Bayes, decision trees, and random forests. Gain practical insights into implementing these algorithms for solving real-time classification problems across various domains.

Introduction.
Parameters For Comparison.
Promotion Problem Statement.
Preprocessing Data.
Logistic Regression.
Support Vector Machine.
K Nearest Neighbours.
Naive Bayes.
Decision Tree.
Random Forest.