Micheal<3 (rough dom)'s Persona: 
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ables into a new set of uncorrelated variables called principal components. The main goal of PCA is to reduce the dimensionality of the data while retaining as much information as possible.
You: what is it
Micheal<3 (rough dom): It seems like you're asking about the concept of Principal Component Analysis (PCA) again. As I mentioned earlier, PCA is a statistical technique used to transform a set of correlated variables into a new set of uncorrelated variables called principal components.
You: yeah
Micheal<3 (rough dom): I'm glad you're interested! PCA is a powerful tool in data analysis and machine learning. It helps to simplify complex datasets by reducing the number of variables while retaining most of the information.
You: Let’s pretend we’re on the metric system and use kilograms instead of pounds to give us a starting base number of 100. Four people (Alex, Brook, Chris and Dusty) want to cross a river in a boat that can only carry 100kg. Alex weighs 90kg, Brook weighs 80kg, Chris weighs 60kg and Dusty weighs 40kg, and they have 20kg of supplies. How do they get across?
You: Jack is looking at Anne. Anne is looking at George. Jack is married, George is not, and we don’t know if Anne is married. Is a married person looking at an unmarried person?
You: A teacher writes six words on a board: “cat dog has max dim tag.” She gives three students, Albert, Bernard and Cheryl each a piece of paper with one letter from one of the words. Then she asks, “Albert, do you know the word?” Albert immediately replies yes. She asks, “Bernard, do you know the word?” He thinks for a moment and replies yes. Then she asks Cheryl the same question. She thinks and then replies yes. What is the word?
Micheal<3 (rough dom): Yes, a married person (Jack) is looking at an unmarried person (Anne).
Micheal<3 (rough dom): Sure, let's solve this problem step by step.
Micheal<3 (rough dom): The word is "max." Each student received a letter from this word: A (Albert), N (Cheryl), and D (Bernard).
