Using XGBoost for Time Series Forecasting in Python ❌ XGBoost for Stock Price Prediction Tutorial

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Hi there! If you want to stay up to date with the latest machine learning and deep learning tutorials subscribe below. Thank you for your support!

DecisionForest

hey, i have a question. can we measure the r2Score of this? I got a negative r2score. Can I know what is the reason?

hasithahiranrajapaksa

why do you put val into np.array? Why do not you use encoders and scaler before testing?

wojtek

I read in a research paper to predict time series we may use multiple trajectories. Any insight on what these trajectories are in time series and how to calculate these?

anurag

Excellent explaination of XGBoost and it's slimplifed things.

limyong

Do you have relevant experience in machine learning survival analysis? For example xgbse, scikit survival and pycox package in python. I don't know how the data format is handled in this case, also time dependent ROC, calibration and DCA.

ddrikee

Great video.. How do you cater for the case where there's a new major event like the pandemic, because the old trained model wouldn't work anymore? Thanks!

weiyang

Just so I understand: This method 1) doesn't de-trend the data or make it stationary, 2) uses just the current price as the only feature (no rolling window aggregates), correct?

dusanbosnjakovic

This looks great thanks :) just subbed today, loving your channel

roywit

Nice! I have a time series problem where the data is at daily level for 3 years and we forecast for daily level 2 years out. Currently I use Prophet which works well. Prophet takes care of spike events (holidays) and weekly / yearly seasonality. Can I use XGBoost to do this? Your example here is forecasting one step out which will be like forecasting one day out for my case.

morecharacterswithamix

I have 450 points for train data, need to predict for next 10 samples, how can we do train test split

malleswararaomaguluri

10:15 Explanation of Walk Forward Method

vivekrai

Thankyou for sharing. I got error in
pred = xgb_predict(history, test_X[0]) and
X, y = train[:, :-1], train[:, -1].
The error message was "IndexError: too many indices for array: array is 0-dimensional, but 2 were indexed".
Could you please tell me how to resolve this error?

ragendhusr

Good video. Is there a way to predict the unknown future? or how can we adapt the function to this approach?

Thank you.

scienceforyoung

I didn't understand the val object, why did u reshape it.Plz give a clarity.
Thanks

RevenueRocketeers

Can you show the end prediction results please? Would be very useful as a reference point :)

hartejhaer

Thank you for this very helpful video. Much appreciated!

emeline

Great video! Another tool in the ML toolbox. Is this different to the Timeseries Cross validation?

dishydez

i tried to sign up to get the code but failed why ?

lollmao

Great Information. Thank you for your time!!
Once you find the rmse for your train/test model. How can you predict for next 2 years?

Spartanboy

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