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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.
Imputation algorithm means “replacing the Blank values by some values)
Mean imputation
Median Imputation
miss forest
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.
In Machine Learning. Perceptron is an algorithm for supervised classification of the input into one of several possible non-binary outputs