I’m studying machine learning, and I have some issues trying to understand this. I found your video, and although English is not my first language, I can fully understand your explanation. Keep going like that 👍
@@learnwithvichu Thanks a lot, Vishnu. I have already told my friends to subscribe your channel though the number of them is really too small, since I am an introvert person.
Clearly explained the main concept. Thank you. How can I use ANOVA algorithm if each group contains non-equal number of values ? For example: I have only 5 salary data in Samsung, 3 in Google and 6 in Sony. Can I use this algorithm for this kind of situations?
ANOVA can be used to explore the relationship between categorical and numerical variables. It works regardless of whether the variable is dependent or independent.
Sir for applying ANOVA for feature selection, do we need to apply a normality test to demonstrate whether our data follows a normal distribution? Or we can apply for any data set without checking the normal distribution.... could you please clarify it?
For ANOVA, it's generally recommended to check the normality of the residuals rather than the original dataset itself. This validates the assumption of normality required for the ANOVA results to be reliable.
thank you for answering. Q1. one more question if my data is not linear then ANOVA is applicable? Q2. If my population is not normal but the sample size greater than 30 is proven to be normal with the central limit theorem then ANOVA is applicable to the total population?
@@learnwithvichu To check the normality of the residuals means we have to first train a model with this data & get the residuals... But aren't we using ANOVA for feature selection method that is before model training?
![One-Way ANOVA [Analysis of Variance] simply explained](http://i.ytimg.com/vi/mOdYddj5IG8/mqdefault.jpg)
I’m studying machine learning, and I have some issues trying to understand this. I found your video, and although English is not my first language, I can fully understand your explanation. Keep going like that 👍
Wonder full. It's easy to understand keep up the good work.
Outstanding video! Short teaching, but cuts through all the fluff to provide most essential part of ANOVA! Thank you for sharing!!!
please upload more videos of Algorithms... your video are the most understandable I have ever seen
Thanks a lot.... Sure will make more videos
Fantastic video simple, easy, and meaningful. Great job!!!
Pure quality content!
Fantastic 🙌🙌
explanation was really simple, thankyou for such videos
Bro, you have such a teaching talent..well bro keep it up..
Thanks Bro.....😊
Nice
really very clear! Thank you very much!
@learn with vichu, please make a video about t-test. Your explanation just sounds like a boom to me.
I did not get enough support so I stopped making videos.
But just for you.. I am gonna make a video on t-test.
You can expect it by next week.
@@learnwithvichu Thanks a lot, Vishnu. I have already told my friends to subscribe your channel though the number of them is really too small, since I am an introvert person.
@@nailahasan7827 Thanks a lot ..... ☺️
What is feature selection?
@@rishception i
In the same playlists, watch the first video. I explained it in detail.
explained very well!!
good work thanks
Nice mann ..keep the good work going 👏
🔥🔥 nice explanation
Amazing, thank you
Super Bro 🔥🔥🔥
quantity does matter, Only quality
What if we have a categorical inputs and a categorical output? What are the suitable feature selection methods?
In such a cases we can use Chi-Square test. Checkout my video on Chi-Square.
Clearly explained the main concept. Thank you.
How can I use ANOVA algorithm if each group contains non-equal number of values ? For example:
I have only 5 salary data in Samsung, 3 in Google and 6 in Sony. Can I use this algorithm for this kind of situations?
I am making a video on that Dude.. the approach is little different. Will upload the video soon. Thank you.
@@learnwithvichu Did you upload video for this? I am looking for its solution.
ANOVA is used when your target variable is categorical not Continuous !!
ANOVA can be used to explore the relationship between categorical and numerical variables. It works regardless of whether the variable is dependent or independent.
Sir for applying ANOVA for feature selection, do we need to apply a normality test to demonstrate whether our data follows a normal distribution? Or we can apply for any data set without checking the normal distribution.... could you please clarify it?
For ANOVA, it's generally recommended to check the normality of the residuals rather than the original dataset itself. This validates the assumption of normality required for the ANOVA results to be reliable.
thank you for answering.
Q1. one more question if my data is not linear then ANOVA is applicable?
Q2. If my population is not normal but the sample size greater than 30 is proven to be normal with the central limit theorem then ANOVA is applicable to the total population?
@@learnwithvichu To check the normality of the residuals means we have to first train a model with this data & get the residuals... But aren't we using ANOVA for feature selection method that is before model training?
thanks ❤