Normalize the numeric predictors using range normalization in the range of -0.5 to .5 in R. Create dummy variables for the categorical variables that can be used in models that require numerical predictors. The dimension of the data.frame at this point should be (5110 17). Create a random sample of 10 observations that oversamples rows that are positive for stroke with a probability of 95%.
Normalize the numeric predictors using range normalization in the range of -0.5 to .5 in R. Create dummy variables for the categorical variables that can be used in models that require numerical predictors. The dimension of the data.frame at this point should be (5110 17). Create a random sample of 10 observations that oversamples rows that are positive for stroke with a probability of 95%.
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Normalize the numeric predictors using range normalization in the range of -0.5 to .5 in R.
Create dummy variables for the categorical variables that can be used in models that require numerical predictors. The dimension of the data.frame at this point should be (5110 17).
Create a random sample of 10 observations that oversamples rows that are positive for stroke with a probability of 95%.
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