natasha ki dish achi thi ya nhi yeh to bta deteOriginally posted by: MasoomaBukhari
hayye
dkho dkho.. achi epi thi bs aundrella aur natasha ko same ingredient mila to mje tension hogyi 🤪
i m glad akanksha is saved not aundrella😛
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natasha ki dish achi thi ya nhi yeh to bta deteOriginally posted by: MasoomaBukhari
hayye
dkho dkho.. achi epi thi bs aundrella aur natasha ko same ingredient mila to mje tension hogyi 🤪
i m glad akanksha is saved not aundrella😛
Originally posted by: Reenatyzed
natasha ki dish achi thi ya nhi yeh to bta dete
i m glad akanksha is saved not aundrella😛
pta nhi kyu nahi btaya.. ajeeb baat he 😕
they do this usually when the dish is too good but they didnt say anything.. ya edit kr dia hoga
wahi naOriginally posted by: MasoomaBukhari
pta nhi kyu nahi btaya.. ajeeb baat he 😕
they do this usually when the dish is too good but they didnt say anything.. ya edit kr dia hoga
pta hi nhi chala achi thi ya buri
but nuts said in interview na k judges ne kuch nhi bola to edit kese
Originally posted by: Reenatyzed
wahi na
pta hi nhi chala achi thi ya buri
but nuts said in interview na k judges ne kuch nhi bola to edit kese
wo to aksar kehte hen.. jb judges kch ni kehte.. lakin baad me dikhate he k kya kaha...
parhai time 😳 again back to kinda jo likha he usey yaad kro subject..
data mining is extracting previously unknown, implicit patterns/knowledge from large amount of data
data bases -- data cleaning > data warehouse -- data selection > task relevant data -- data mining > pattern evaluation -> knowledge
KDD process -> typical view:
input data -> pre processing (normalization, data integration, feature selection)
-> data mining (cluster analysis, pattern discovery, outliers)
-> post processing (pattern selection, pattern evaluation, pattern interpretation)
major issues in data mining:
-mining methodology -> mining knowledge in multi dimensional space, handling noise, uncertainty and incompleteness of data
-user interaction -> data presentation and visualization
-efficiency and scalability -> e&s of algos
-diversity of data types -> complex data types, global repositories
-data mining & society -> privacy preserving DM, invisible DM
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