Example of Machine Learning Classification technique on Iris Dataset using Logistic Regression
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- Опубліковано 17 сер 2021
- In this video, we will see one of the most popular examples of classification in Machine Learning i.e. Iris Dataset. Video helps you understand how to use Logistic Regression algorithm in Machine learning using Jupyter Notebook.
Decision Tree Classification using Iris Dataset:
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SVM Classification Technique on iris Dataset using Support Vector Machine:
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KNN Classification Technique on iris Dataset using KNN:
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Random Forest classification technique on Iris Dataset:
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Iris Dataset Classification Using Naive Bayes Classifier:
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To understand what is Classification watch below video:
• What is Classification...
Watch the full video to understand the demonstration of Classification on the Iris dataset in detail.
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Free Code uploaded to GitHub repositry link:
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Came here for the confusion matrix explanation in this context and was not disappointed. Cheers!
Thank you,
What other topics you want me to create videos on?
Thank you so much for making this video. 👍👍👍
Thank you, which other tutorials you want to see?
perfect short explained... thank you so mucgh...love from kolhapur, maharashtra ....
Thanks a lot 🙏
Amazing! greetings from Argentina 💪
Thank you 🙌
Very nice 👍🏽
Thank you so much it helped me a lot sir
Anytime... :-)
No fancy codes nothing hard, just simple techniques and easy to understand.
But still waiting for your next video on this series :(
Thank you 🙏🏻, soon we are uploading more and more videos
when i try to map the species column with numerical values and print the data head after mapping it is showing all values as nan in species column, i tried everything but it is not getting solved
please tell me how image datasets convert into 0,1 ,2 ,3 etc form for confusion matrix...... im facing lots of problems because i am fitting the model in image form but unable to create confusion matrix... error is "Classification metrics can't handle a mix of multiclass and unknown targets" this error is coming ...please help....
I tried to use the map function to convert the categorical variables into numerical but when i print out the set the species column shows NaN instead of 0,1 or 2. Not sure what the problem is
What you did
github.com/eduai-repo/ML-Demo/blob/main/2%20Classification/1.%20Logistic%20Regression-%20Iris%20Dataset.ipynb
try this code, let us know if it works
After mapping with integer value it showing Nan values for species
nope, it's not Nan, it's 0, 1 or 2.
ML doesn't understand categorical data, to process classes we've used mapping
flower_mapping = {'setosa': 0,'versicolor': 1,'virginica':2}
Try this code : github.com/eduai-repo/ML-Demo/blob/main/2%20Classification/1.%20Logistic%20Regression-%20Iris%20Dataset.ipynb
the mapping function is showing Nan values for the species column???
nope, it's not Nan, it's 0, 1 or 2.
ML doesn't understand categorical data, to process classes we've used mapping
flower_mapping = {'setosa': 0,'versicolor': 1,'virginica':2}
Try this code : github.com/eduai-repo/ML-Demo/blob/main/2%20Classification/1.%20Logistic%20Regression-%20Iris%20Dataset.ipynb
@@AsifImmanad tried this but still its showing Nan value sir
@@GemsofPakistan1 Our code is uploaded on github repository, you can download link is in the pinned and also in the video description
the iris.csv file in the kagle get a new update after that the problem started map function giving null value can you help to solve the problem🙂
I need to check your code,
Try with my code, uploaded on github repository- github.com/eduai-repo/ML-Demo
tahnkyou sir i found the error it is happening because the names in the file was updated the code is correct just need to put right name @@AsifImmanad
from where can i download the dataset
@@prakratisahu4707
github.com/eduai-repo/ML-Demo
Pls just share code and dataset also.. if you can
Sure, We’ll upload on github and provide you the link in our community tab soon, keep eye on next video and community tab