Coding a Decision Tree from Scratch in Python p.2: Helper Functions

In this video series we are going to code a decision tree classifier from scratch in Python using just numpy and pandas. And in this video we are going to build the first two helper functions which we are going to need to run the decision tree algorithm.

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edit: at 13:51 I meant to say “two” not “zero”

[rajatpati]

Great effort from you. I have searched lot of videos in youtube but no one has ever explained this algorithm without use of sklearn as per my knowledge. It will help people to writing their own customised Machine Learning Algorithm. Hope to learn a lot from you.

[asma-perx]

A great effort.And thanks a lot because you were the only one who actually explained the algorithm instead of showing how to use functions from any modules to do the above task which is shown by many people in YouTube.

[andrewwilson]

Hi, I have an assignment due tomorrow and was getting very overwhelmed with understanding the implementation of this, until I found your video. Thank you! You genuinely saved me from so much stress

[ahmadmponda]

This is indeed unique style from the entire youtube i've ever watched.Excellent OO methods.

[divya]

You are a genius You've taught exactly what anyone would be looking for.

[heroicrhythms]

Sebastian, you are doing a very great job, please keep going, even great endings have small beginnings.

[LMGaming]

You still saving people in 2020 ! thanks

[valerysalov]

do you have a patreon account? This is the best explaination I have ever seen it's not just about decision tree but minute caveats like train_test_split something we take for granted when calling for sklearn, thank you so much from the bottom of my heart, would love you to do more of this like gbdts, adaboost, lda, pca etc

[Divine_Inspired]

One of the best lecture i found .Thanks man

[SophieBergerCreates]

Amazing tutorial, exactly what I was looking for

[antonyrobert]

Hi Sebastian, this is an excellent video! I just wanted to know the kind of decision tree that you have built above? Is it an ID3, CART or a C4.5? Thanks!

[hopelesssuprem]

Thank u for a great tutorial. Is it a CART version?

[sounakmojumder]

please make more videos your contents are very good

[exoticme]

i learned to make a DST using entropy and info gain. Now, im doing assignment to make a categorical DST for iris dataset. I have converted the numerical values to categories on some ranges. Will your code also work for them the same, ofxourse with a bit modification of placing the numerics with categories?

[zeroes_ones]

Hi Sebastián, how did you come up with petal_width less than 0.8 will fetch the pure class?