Machine learning models are created using linear discriminant analysis, a supervised classification method. These dimensionality reduction methods are employed in a variety of applications, including marketing predictive analysis and picture identification.
Before classification, linear discriminant analysis is performed to reduce the number of features to a more manageable quantity. Each of the additional dimensions is a template made up of a linear combination of pixel values.
The goal of LDA is to use a linear discriminant function to maximise between-class variance and reduce within-class variance under the assumption that data in each class is characterised by a Gaussian probability density function with the same covariance.
This one is one of the best online free source to study the coding or any particular course.
H
happy
4
Course is nice but where is the link for installation of Anaconda
D
Digvijay Kewale
4
Course is good understandable but I am not able to download resources (one star less only for this not able to download resources)
S
Shivendra Shahi
5
I am impresses by the way of teaching, what a magical teaching skill he has.
S
Sandeep Kumar
5
good content with free of cost
Sucheta Kumari
5
Course content and explanation method is just awesome. I like the way they presenting and specially at the end of each video content they feeding next intro content which makes motivated, excited .
Share a personalized message with your friends.