CS 7646: Decision Trees Part 1 (new location)

[@makeshiftpenny]

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

[@connorelkin7115]

very helpful for the midterm, thanks!

[@sagniksinha5831]

Extremely helpful

[@graceb2404]

Thank you for your service my man

[@PippyPappyPatterson]

🫡

[@alexwilson6136]

Content starts around 11:05

[@awayahshahid8006]

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

[@xMercuryx56]

40:17 i spat my food out

[@AminShahGilani]

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

[@nickzkr]

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.

[@tyghaZ]

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

[@rendybjunior]

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. kzbin.info/www/bejne/jYfGZJagq6l7ntk 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.

[@BenHizak]

What is this toy called?

[@RoadToSalvationX]

Well explained, thank you.

[@vikashkerketta6986]

How was the correlation calculated ? around 28:30

[@awayahshahid8006]

using an in built excel function

[@lihanlive]

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

[@ShaunPatterson]

Paying attention Mr. Abercrombie?

[@mohinderlamba]

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

[@nickcorona3966]

Why is it terrible delivery?