I think that because RandomForest is a classification algorithm so classification metrics such as accuracy, roc&auc , confusion metrics can be used to assess the model.
Thank you for your good explanations and experience based valuable suggestions. You claimed that Random Forest based segmentation is better than that of SVM. Do you have a chance to test XGBoost? If no then I strongly suggest it.
Yes, I did experiment with a few boosting techniques including XGBoost. It is a good approach but the accuracy depends on hyperparameters. I thought I recorded a video on this topic but apparently I haven't. Thanks for the suggestion, I am sure the viewers of this channel would like to know more about it.
Dear. I do appreciate your lecturing style. I have two questions- "How to measure the performance of Random Forest?". What metrics are used to compare it to other algorithms?
I think that because RandomForest is a classification algorithm so classification metrics such as accuracy, roc&auc , confusion metrics can be used to assess the model.
Sir. How to measure its performance?
I think that because RandomForest is a classification algorithm so classification metrics such as accuracy, roc&auc , confusion metrics can be used to assess the model.
How do we know the pixel value?
Thank you for your good explanations and experience based valuable suggestions. You claimed that Random Forest based segmentation is better than that of SVM. Do you have a chance to test XGBoost? If no then I strongly suggest it.
Yes, I did experiment with a few boosting techniques including XGBoost. It is a good approach but the accuracy depends on hyperparameters. I thought I recorded a video on this topic but apparently I haven't. Thanks for the suggestion, I am sure the viewers of this channel would like to know more about it.
Dear. I do appreciate your lecturing style. I have two questions- "How to measure the performance of Random Forest?". What metrics are used to compare it to other algorithms?
I think that because RandomForest is a classification algorithm so classification metrics such as accuracy, roc&auc , confusion metrics can be used to assess the model.
dear sir .. number of decison tree are equal to number of input features ?
so i have watched your videos from 1 upto thus far, you have not shown how to LABEL the image
Is it necessary to create a bootstrap dataset?
Your videos is very good one. Thanks very much man. Do you give the permission to use your exemples and code to recorde a Portuguese videos?
If you want to add Portuguese voice over please let me know. I guess, it can help some users.
Python for Microscopists by Sreeni . No no...The idea is record my own video. Just use your code exemples.
Awesome info
great video!
Thanks
Can this be applied to HeLa Cell segmentation?
Yes. The exact application doesn't matter.