Baggingis a homogenous parallel method sometimes calledbootstrap aggregating. It uses modified replicates of a given training data set to train multiple base learners with the same training algorithm.12Scikit-learn’s ensemble module in Python contains functions for implementing bagging, such as BaggingC...
Frequently Asked Questions (FAQs) 1. What is meant by overfitting and underfitting data with examples? 2. What are the methods to avoid overfitting and underfitting in machine learning? 3. How are bias and variance related to underfitting and overfitting in machine learning?
LDA’s imagined generative text process begins with pre-document topics. Each topic is fixed vocabulary of words, in which each word has a probability that it belongs to that topic. Note that words are assigned probabilities rather than a discrete category to account for potential plurality of m...