Menu
I have an ARFF file containing 14 numerical columns. I want to perform a normalization on each column separately, that is modifying the values from each colum to (actual_value - min(this_column)) / (max(this_column) - min(this_column)). Hence, all values from a column will be in the range [0, 1]. The min and max values from a column might differ from those of another column.
How can I do this with Weka filters?
Thanks
493
The purpose of normalization is, primarily, to scale numeric data from different columns down to an equivalent scale. For example, suppose you execute the LINEAR_REG function on a data set with two feature columns, current_salary and years_worked . The output value you are trying to predict is a worker's future salary.
Scaling just changes the range of your data. Normalization is a more radical transformation. The point of normalization is to change your observations so that they can be described as a normal distribution.
This can be done using
weka.filters.unsupervised.attribute.Normalize
After applying this filter all values in each column will be in the range [0, 1]
77
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
