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>>>>>>Data Scientist Tricky Interview Questions
##### When to use Logistic Regression and when to use Linear Regression?
If you are dealing with a classification problem like (Yes/No, Fraud/Non-Fraud, Sports/Music/Dance) then use Logistic Regression.
If you are dealing with continuous/discrete values, then go for Linear Regression.
##### What are the different imputation algorithm available?
Imputation algorithm means “replacing the Blank values by some values)
Mean imputation
Median Imputation
MICE
miss forest
Amelia
##### What is AIC(Akaike Information Criteria)
The analogous metric of adjusted R² in logistic regression is AIC.
AIC is the measure of fit which penalizes model for the number of model coefficients. Therefore, we always prefer the model with minimum AIC value.
##### Suppose you have 10 samples, where 8 are positive and 2 are negative, how to calculate Entropy (important to know)
E(S) = 8/10log(8/10) – 2/10log(2/10)
Note: Log is à base 2
##### What is perceptron in Machine Leaning?
In Machine Learning. Perceptron is an algorithm for supervised classification of the input into one of several possible non-binary outputs