Data clustering algorithms such as k$-$means clustering requires that features be normalized to the same range. Consider that a genetic algorithm will be used to cluster structured data, where the representation scheme on slide $14$ of EAforDA.pdf is used. Each individual $($chromosome$)$ therefore contains an assignment of cluster identifiers to the instances in the dataset. It is then not necessary for this genetic algorithm approach to data clustering that feature values be scaled to the same range. The fitness function is the quantization error, which has to be minimized. Think carefully.

Question $1$Select one:

True

False