missing values
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visualizing missing values.
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imputing data set selection.(the picture is very important.)
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just few missing values by particular model
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predicting values based on other variables
model testing
- OOB error
The black line shows the overall error rate which falls below 20%. The red and green lines show the error rate for ‘died’ and ‘survived’ respectively.
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RMSE
LASSO MODEL
THE MOST POPULAR ALGORITHM
THEN WE COULD COMPARE THEM BY RMSE AS FOLLOWS
variable importance
variable selecting
- Boruta Feature Importance Analysis
- Plotting all data
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Explore the correlation
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Plot scatter plot for variables that have high correlation.(the same link as 3th)
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some useful plot
