What do you mean by Data leakage and how does it affect the model performance if we take the average of all values from the dataset as you mentioned at 10:50
Hey, nice explanation on how catboost does categorical encoding during training which makes it robust to overfitting and also faster but there is another very important feature 'ordered boosting' of catboost which i think you could cover. I was reading the paper but couldn't grasp it properly. Anyways thanks for the video :)
Hi Aman, thanks for sharing the video. nice explanation. Helps a lot. One question on categorical var encoding, i understand the training data part (you made it easy!) but curious to know how it is done in test set. Is it mean/median of the numeric encoded values for each category of a category var in the training set? Thanks
Thanks for the New concept. Can we use this Catboost for Text Classification and Time Series. And please upload the Python code implementation for the Catboost.
Hello Aman, thanks for the sharing the details I have quick question on data encoding for Nominal data, which one will select among list of the encoding techniques ? One-hot/dummy encoding. Label / Ordinal encoding. Target encoding. Frequency / count encoding. Binary encoding. Feature Hashing.
If my data consists of both categorical and numerical feature can i implement catboost directly . coz in the error it says that it has to be str or an int only
A fantastic video that explains catboost so well! I wish I had seen it before the last tech interview...
What do you mean by Data leakage and how does it affect the model performance if we take the average of all values from the dataset as you mentioned at 10:50
Watch thois Tanmay
th-cam.com/video/yuOOo0FQklQ/w-d-xo.html
yes plz make video on python implementation of lightgbm and cateboost .. with time series implementation and hyper parameter implementation
Video is created Mohit. Please look on the channel for "xgboost vs catboost vs lightgbm"
Hey, nice explanation on how catboost does categorical encoding during training which makes it robust to overfitting and also faster but there is another very important feature 'ordered boosting' of catboost which i think you could cover. I was reading the paper but couldn't grasp it properly.
Anyways thanks for the video :)
Welcome OM 🙂
This is truly a fantastic explanation!
can we also expect practical implementation for the same..
It's there, search for catboost vs lightgbm vs xgboost
What writing you are using ?
Hi Aman, if encoding is different for every row how the category will be encoded at the time of prediction.
Thanks!! Would be very appreciated if you could do a video in which you implement CatBoost with Cross Validation in python!!
Hi Aman, thanks for sharing the video. nice explanation. Helps a lot. One question on categorical var encoding, i understand the training data part (you made it easy!) but curious to know how it is done in test set. Is it mean/median of the numeric encoded values for each category of a category var in the training set? Thanks
Please create a video of cat boost mathematics
Can u please tell me what is purpose of using catboostregression ?
Nice explanation. Thanks Aman.
Welcome Radha.
Thanks for the New concept. Can we use this Catboost for Text Classification and Time Series. And please upload the Python code implementation for the Catboost.
Welcome. Yes we can use. Sure
Hello Aman, thanks for the sharing the details
I have quick question on data encoding for Nominal data, which one will select among list of the encoding techniques ?
One-hot/dummy encoding.
Label / Ordinal encoding.
Target encoding.
Frequency / count encoding.
Binary encoding.
Feature Hashing.
Well explained
Thank you
if threre is no cator. variable then we dont need to do pooling ??
I dont think so
can catboost and lightgbm algo used for time series forecasting plz tell me ?
Yes possible
If my data consists of both categorical and numerical feature can i implement catboost directly . coz in the error it says that it has to be str or an int only
In the pipeline mention which ones are categorical columns.
Check my implementation video, I hv done it.
Video title "catboost vs xhboost vs lightgbm"
Broi..is this relevant outside russia??