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Voting Classifier : Hard Voting and Soft Voting Explained with Examples in Hindi ll Machine Learning 

5 Minutes Engineering
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Myself Shridhar Mankar an Engineer l RU-vidr l Educational Blogger l Educator l Podcaster.
My Aim- To Make Engineering Students Life EASY.
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11 сен 2024

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Комментарии : 34   
@aditiabhang9622
@aditiabhang9622 5 лет назад
Make video on Ada Boost and Gradient Tree Boosting plzzz
@omihalikar7799
@omihalikar7799 5 лет назад
Voting to computing, that escalated quickly :) 4:10 Great videos BTW.
@ramalfatima8135
@ramalfatima8135 Месяц назад
You are great way of teaching thank you for making machine learning easy for us .please make a video for deep learning concepts as well
@reddipradeep2768
@reddipradeep2768 9 месяцев назад
One of the finest explanation I have seen on youtube❤
@dhananjaykansal8097
@dhananjaykansal8097 5 лет назад
Lovely Lovely!!!!
@ayushijmusic
@ayushijmusic 4 года назад
Best explanation. Thankyou
@nachiketpj2112
@nachiketpj2112 5 лет назад
Sir please uplod 6th unit of ML
@shubhangiimohite7594
@shubhangiimohite7594 2 года назад
Thank you sooo much sir..
@priyakhedekar184
@priyakhedekar184 5 лет назад
Thanq sir. Plz make vdo on decision tree gini index
@angelbythewings
@angelbythewings 3 года назад
Loved it man
@tekbistbithari4090
@tekbistbithari4090 3 года назад
What happens if we have two classifiers and two binary classes......if both classes gets one vote then which class would be predicted in hard voting
@vishalgour8947
@vishalgour8947 2 года назад
He doesn't know it.... I think!!!!
@tusharnagda7141
@tusharnagda7141 Год назад
what if the average of predictive probabilities are equal or the count in hard voting are same?
@prasaddalavi9683
@prasaddalavi9683 Год назад
What I think is in case of hard voting, the design of ensembling model is done in such a way that equal condition won't arise. If we use odd number of classifiers it will resolve the issue. In case of soft voting, it is very rare to have 0.5 probability from all the classifiers. If this case happens we can have confidence threshold saying that if any of the classes were predicted with above 0.5 average probability then only we are going to consider that classification as successful and considerable. Else we can say that model is not confident about predictions
@achin_sharma
@achin_sharma 7 месяцев назад
decision function and predict proba hai naa
@shrutimate8155
@shrutimate8155 5 лет назад
Make videos on cloud computing
@61_shivangbhardwaj46
@61_shivangbhardwaj46 3 года назад
Thnx sir😊
@shreyaldevadhe8647
@shreyaldevadhe8647 5 лет назад
Sir please upload the next topic of 4th,5th and 6th units
@vikramkumar-ns5xu
@vikramkumar-ns5xu 5 лет назад
Cloud computing Mai Xen, VMware,EC2 wagera pe lecture video nhi hai sir
@asadmahmood4873
@asadmahmood4873 2 года назад
Nice bro
@simk8979
@simk8979 5 лет назад
Gradient tree boosting ka video please
@YashYadav-xk4wl
@YashYadav-xk4wl 5 лет назад
Abki baar Modi sarkaar..😂
@deepmala1006
@deepmala1006 3 года назад
Anyone plz explain soft voting
@mehrnazasadi2149
@mehrnazasadi2149 4 года назад
why do you write the title in English if the video is not English?
@aahiljunaidnext
@aahiljunaidnext 3 месяца назад
Bahumat toh INDI ALLAINCE ko milega
@prasadnarode8081
@prasadnarode8081 5 лет назад
Shayad thoda galat hogaya... Soft voting me weights assign karne k baad Probability ko multiply hote he and then 0 and 1 ki values se class decide hota he
@5MinutesEngineering
@5MinutesEngineering 5 лет назад
In Video I Considered Uniform Weights, We Can Also Assign Different Weights to Classifier and Compute the same as you said in comment.
@prasadnarode8081
@prasadnarode8081 5 лет назад
Exactly,so if the weights differ, the classifier can give diffrent answers.. 0 can become 1 and 1 can become 0..
@5MinutesEngineering
@5MinutesEngineering 5 лет назад
Yes that's Possible depending on the weights that we assign to classifiers.
@fiddinyusfida5356
@fiddinyusfida5356 5 лет назад
@@5MinutesEngineering Is there any rules about how we assign the weight for every classifier?
@anarosafloresgarcia5654
@anarosafloresgarcia5654 5 лет назад
alguien que lo traduzca? :(
@shaiksuleman3191
@shaiksuleman3191 4 года назад
Those who unlike they are outliers
@vaibhavkhalane5217
@vaibhavkhalane5217 5 лет назад
Please use a mic
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