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pygad/pygad.py

@@ -83,7 +83,7 @@ def __init__(self,
         init_range_high: The upper value of the random range from which the gene values in the initial population are selected. It defaults to -4. Available in PyGAD 1.0.20.
         # It is OK to set the value of any of the 2 parameters ('init_range_low' and 'init_range_high') to be equal, higher or lower than the other parameter (i.e. init_range_low is not needed to be lower than init_range_high).
 
-        gene_type: The type of the gene. It is assigned to any of these types (int, float, numpy.int8, numpy.int16, numpy.int32, numpy.int64, numpy.uint, numpy.uint8, numpy.uint16, numpy.uint32, numpy.uint64, numpy.float16, numpy.float32, numpy.float64) and forces all the genes to be of that type.
+        gene_type: The type of the gene. It is assigned to any of these types (int, numpy.int8, numpy.int16, numpy.int32, numpy.int64, numpy.uint, numpy.uint8, numpy.uint16, numpy.uint32, numpy.uint64, float, numpy.float16, numpy.float32, numpy.float64) and forces all the genes to be of that type.
 
         parent_selection_type: Type of parent selection.
         keep_parents: If 0, this means no parent in the current population will be used in the next population. If -1, this means all parents in the current population will be used in the next population. If set to a value > 0, then the specified value refers to the number of parents in the current population to be used in the next population. Some parent selection operators such as rank selection, favor population diversity and therefore keeping the parents in the next generation can be beneficial. However, some other parent selection operators, such as roulette wheel selection (RWS), have higher selection pressure and keeping more than one parent in the next generation can seriously harm population diversity. This parameter have an effect only when the keep_elitism parameter is 0. Thanks to Prof. Fernando Jiménez Barrionuevo (http://webs.um.es/fernan) for editing this sentence.