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Machine learning work flow (1.Data cleaning (a. Normalisation…
Machine learning work flow
1.Data cleaning
Train and test split
Missing values
imputer and strategy
a. Normalisation
Normalization
standardisation
binarization
encoding category variable
feature creation :polnomial
Model creation
prediction
Fitting
model creation
Evaluation
classification metrics
Accuracy confusion metrics classification report, F1
regression metrics
MAE, MSE, R2
clustering metrics
Homogenity Adj.Rank.index V-measure
Tunning
randomised parameters
Grid search