Another important approach for dealing with missing data is multiple imputation. Instead than substituting a single value for each missing data point, multiple imputation replaces the missing values with a variety of probable values that account for the natural variability and uncertainty of the right values.
Imputation is the process of replacing missing data with replaced values in statistics. It's called "unit imputation" when substituting for a data point, and "item imputation" when substituting for a component of a data point.
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Shafi Akhtar
5
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Aniket Kumar prasad
5
Very helpful and easy to understand all the concepts, best teacher for learning ML.
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Rishu Shrivastav
5
explained everything in detail. I have a question learnvern provide dataset , and ppt ? or not?
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VIKAS CHOUBEY
5
very nicely explained
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Vrushali Kandesar
5
Awesome and very nicely explained!!!
One importing thing to notify to team is by mistakenly navie's practical has been added under svm lecture and vice versa (Learning Practical 1)
M
Mohd Mushraf
5
Amazing Teaching
J
Juboraj Juboraj
5
Easy to understand & explain details.
J
Joydeb
5
Awesome Course sir and your teaching style is very GOOD.
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Shaga Chandrakanth Goud
5
Hi Kushal ji, Thanks a lot for a very good explanation. I have doubts about where we can get the dataset that you explained in the video. Can you make it available in resource ,so that we can downld
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Neel Khairnar
5
Kushal is very good explainer he is covering all topics nicely 👍
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