Thank you for tutorial sir but I have a question. How can we predict the new classifications for a new data whish the results haven’t yet been seen? I would be really happy if you can make a short tutorial about it. All tutorials are measuring the performance of test data and leaving it there. In real life, it is important to work on datas which their classes havent yet been seen.
There is what we call "model training and validation" . During this phase, you train the model based on the features/variables specifically on your dataset. After training the model, you need to evaluate its performance and accuracy and if it results to high accuracy, you now have a predictive model that can be used on a new dataset. But you need to make sure that your new dataset still has the same features/variables or else the results will be most likely inaccurate.
For confusion make sure the data type of the two input is the same. You can use as.factor() to convert them before you pipe into the confusion matrix function
Woow so grateful to this video, very important for me and it saved me out of days of struggling.
hi Mukhtar please can you help me with R?
This is super helpful and informative, thank you.
Thank you for tutorial sir but I have a question. How can we predict the new classifications for a new data whish the results haven’t yet been seen? I would be really happy if you can make a short tutorial about it. All tutorials are measuring the performance of test data and leaving it there. In real life, it is important to work on datas which their classes havent yet been seen.
yes i also have a same question.
There is what we call "model training and validation" . During this phase, you train the model based on the features/variables specifically on your dataset. After training the model, you need to evaluate its performance and accuracy and if it results to high accuracy, you now have a predictive model that can be used on a new dataset. But you need to make sure that your new dataset still has the same features/variables or else the results will be most likely inaccurate.
Im getting this error
Algorithm did not converge in 1 of 1 repetition(s) within the stepmax.
Hi sir, when I use the confusion matrix, an error appears: should be factors with the same levels. How to solve the problem? thanks
For confusion make sure the data type of the two input is the same. You can use as.factor() to convert them before you pipe into the confusion matrix function
@@LiquidBrain this DOES NOT work. what to do????
Thank you so much
Hi sir,
Can I get a R code for ANN model for forecasting streamflow.
Not sure what kinds of ANN you are looking for, but there's a RNN videos you might be interested on the channel
Nice
Hi. Was working, no longer working
pred.2$X1L
Thank you sir!!!!!!!!
hi sir, can i have the source code please.. for my school.project
Thanks bro
Hi. Can I have your email address for some question and more information bout writing codes with battery datasets and my concerns? Thank you
This is for the engagement
your accent and pace makes it really hard to understand some words