Implement Decision Tree in Python using sklearn|Implementing decision tree in python

sir data ki link nahi ha isma

Can you provide us with the dataset you used in this video?

Hello sir, thanks for such a wonderful video. are you a data scientist?

Can you show us the tree visually using plot or graphviz .just want to see the values in decision tree node and interpret decision rules

can you provide dataset and code?
it will be helpful

Thank you so much for this great video!!!!

Can u send me link of the dataset plz

Thank you so much! So glad I found this video and your channel! I do have one question: your max leaf nodes are set at 10, and there are 10 independent variables in the data you input into the model. Is that a coincidence, you should your max leaf nodes always match the number of IV's? Thanks again!

post the dataset

Please share drive link for the datsets . It's not in description. Thank You

Great lecture. Please where is the next video? I searched your page

Where to get the source code ?

Can I get code

you have deleted the dataset? it is no longer available..

amazing!

any video on how to extract rules in text from an existing decision tree ??

good work

please provide dataset link whenever you do project

Sir, how excel file data was uploaded in python program

Sir I got a assignment but I don't know what should I use like I should use decision tree or linear regression so can you please help me please

could you pls share the code?

Thank you for doing this!

Sir can you send data set

why didn't you prune the data for more accuracy?

Where did you get the dataset?

I am unable to use the sklearn command in vsc

For anyone using PyCharm, data.head will not work. Use the print function: print(data.head)

can you provide the dataset

Thanks for the video please share some videos related to signature based intrusion detection

bro I need code and dataset of weather data classification using decision trees?

Wow! That's so crisp & clear explanation, to the point! I really appreciate your simplicity, that's your power. Thanks!

Thanks for the explanation, your'e better and much more clearer than my university lecturer

I am unable to find the ipynb notebook in the google drive for practice which is vital. Please guide

did u remove relative_humidity_3pm from in [41] ? i didnt get that

Can you link your notebook?

amazing explanation , can you please give me the whole code

This was a great video....Also make a video on how to increase the accuracy of the decision tree by hyper parameter tuning...That would be helpful.....Looking forward to that video

Sir I don't find the weather data set used in this vedio in the Google Drive instead I found other data sets
Please share the data set used in this vedio

while running
humidity_classifier.fit(X_train,y_train) command
i am facing this error
AttributeError: 'DecisionTreeClassifier' object has no attribute '_validate_data'
Could you help me out

hi sir , i want this dataset which you explained in this video sir

Very nice

Thank you the explanation, much better than my professor!
I had a question, I am getting what I think is an error, when I change the max_depth argument in the DecisionTreeClassifier from 1 to None, my accuracy score doesn't change and neither does my .score
How can I fix this and do you have any idea why it may be happening?

Can you share the code github link please?

This was very very very very helpful, thank you very much for taking the time to make and upload this video. Greatly appreciated from Brighton, England :D

Using sklearn is very easy. Try from scratch

amazing video ... can you tell me how you decide leaf no to be 10 to avoid overfitting..

Great explanation, thanks for the video

Hi, i was wondering why random_state=324?

X_train,X_test,y_train,y_test = train_test_split(x,y,test_size=0.33,random_state=324)