CS 7646: Decision Trees Part 1 (new location) 

11:00: Factors (X1, X2, …, XN) 15:00: describing decision tree structure 16:30: theme of lecture: how to use a decision tree if you have one 19:00: Decision tree API 22:00: introduce UCI wine dataset 24:00: Discussion of wine dataset 27:00: abstracted model dataset with X_n factors and y label 30:30: how to use a decision tree 32:00: gap while drawing decision tree (skip) 36:30: example decision tree with quiz 41:00: answer to quiz 44:00: in-sample vs out-of-sample testing --> overfitting • y_predict = model's predicted y value • y_test = true value (out-of-sample test) 48:00: implementing decision tree as ndarray 1:00:00 - Saving tree data to an ndarray - use relative indexes for children • Think about binary tree indexing parent & children nodes 1:01:40: Q&A • Fastest time-to-query: linear regression --> decision tree --> KNN • Max time-to-query for decision tree: log_2 (n) where n = number of nodes (assuming a balanced tree) • Decision trees are slow to learn/train --> it takes a lot of computational time to build a decision tree 1:07:00: end of lecture

Content starts around 11:05

This was a great lecture for helping build intuition about decision trees. Thank you Prof Balch! You're awesome!

it could more helpful, if we could see the full whiteboard

At 1:04:39 she says log2(100) which is 6.643856189774724

If you already have rough idea on how decision tree works, I suggest you to jump to part 2 where the algorithm on how to construct the decision tree is being explained, to save your time. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-WVc3cjvDHhw.html As the sound quality in this video is not great, it is hard to grasp exact words from the professor and I end up guessing what is it about from the whiteboard.

If you don't care to hear an initial analogy about the game "20 Questions", then you can start the lecture around the 20 minute mark.

Well explained, thank you.

thank you for it first, I have to say this can be improved to much better.

40:17 i spat my food out

How was the correlation calculated ? around 28:30

What is this toy called?

Paying attention Mr. Abercrombie?

terrible delivery I am sorry to say. I had to listen at 1.5 speed and yet could not tolerate it.