@@obaagela5191 In case you're still wondering about this, datacamp is a website with a huge variety of courses on R, python, machine learning and a whole host of other subjects. This video will be a part of one of those courses so after the video it will take you to an in browser IDE where it will run you through the steps of doing the cross validation yourself. There's a free trial available and I highly recommend it.
It doesn't matter what you set the seed to, it just ensures that you will always generate the same output using the subsequent code. It could have been set to 100 or 3 or anything else - as long as you don't change the seed you're good.
42 is the answer to the Universe. Kidding aside, it's just a way that someone can duplicate your results exactly. It generates "random" numbers still; however, they are the SAME random numbers every time. Anyone should be able to exactly reproduce your code if they set the seed exactly how you set it.
But this begs the question. What does the right cheek clap
Where is the continuation of this video please
pay for it
Angela, we don't have to pay for it, we have to practice it by ourselves I suppose ;o)
@@fahimaljahangir3059 haha
@@fionareiki1493 ohk got ya! Thanks
@@obaagela5191 In case you're still wondering about this, datacamp is a website with a huge variety of courses on R, python, machine learning and a whole host of other subjects. This video will be a part of one of those courses so after the video it will take you to an in browser IDE where it will run you through the steps of doing the cross validation yourself. There's a free trial available and I highly recommend it.
why set the random set to be 42
It doesn't matter what you set the seed to, it just ensures that you will always generate the same output using the subsequent code. It could have been set to 100 or 3 or anything else - as long as you don't change the seed you're good.
42 is the answer to the Universe. Kidding aside, it's just a way that someone can duplicate your results exactly. It generates "random" numbers still; however, they are the SAME random numbers every time. Anyone should be able to exactly reproduce your code if they set the seed exactly how you set it.
You can give any value for the seed. If you give same seed value any other time you may get same data which collects randomly
Setting the seed in R allows you to test over and over with the same data. The actual value you use is arbitary. You can use any value
I didn't understand shit!