When using Gaussian mixture model, how do you know it is applicable
Upasana | May 24, 2019 | 1 min read | 3 views
Answer :
Assumption we take before applying Gaussian Mixture Model is that data points must be Gaussian distributed means their probability distribution must be Gaussian Distribution which means, We won’t be taking only mean into consideration but standard deviation as well of each cluster.
For optimizing this model, EM (Expectation Maximization) algorithm is used.
Top articles in this category:
- RuntimeError: get_session is not available when using TensorFlow 2.0
- SVM after LSTM deep learning model for text classification
- Configure Logging in gunicorn based application in docker container
- Google Data Scientist interview questions with answers
- Introduction to regression, correlation, multi collinearity and 99th percentile
- Why use feature selection in machine learning
- Derivative of 1/x & Tossing a coin problem
Recommended books for interview preparation:
Book you may be interested in..
Book you may be interested in..
