Lecture-47: Linear Discriminant Analysis (LDA) with Python
In this video, I explained Linear Discriminant Analysis (LDA). It is a classification algorithm and Dimension reduction technique.
-Linear Discriminant Analysis (LDA) is most commonly used as a dimensionality reduction technique in the pre-processing step for pattern classification and machine learning applications. The goal is to project a dataset onto a lower-dimensional space with good class separability in order to avoid overfitting (“curse of dimensionality”) and also reduce computational costs.
-Dataset link
https://www.kaggle.com/datasets/uciml...
-Lecture-42: Dimensionality Reduction: Principal Component Analysis (PCA) (Part-I)
• Lecture-42: Dimensionality Reduction: Prin...
-Lecture-43: Principal Component Analysis - (Part-II)
• Lecture-43: Principal Component Analysis ...