def main(argv):
# Select optimizers
# "SSA","PSO","GA","BAT","FFA","GWO","WOA","MVO","MFO","CS","HHO","SCA","JAYA","DE"
optimizer = ["SSA", "PSO", "GWO"]
# Select benchmark function"
# "F1","F2","F3","F4","F5","F6","F7","F8","F9","F10","F11","F12","F13","F14","F15","F16","F17","F18","F19"
# "Ca1","Ca2","Gt1","Mes","Mef","Sag","Tan","Ros"
objectiveFuncs = ["F3", "F4"]
# Select number of repetitions for each experiment.
# To obtain meaningful statistical results, usually 30 independent runs are executed for each algorithm.
NumOfRuns = 3
# Select general parameters for all optimizers (population size, number of iterations) ....
params = {"populationSize": 30, "iterations": 50}
# Choose whether to Export the results in different formats
exportFlags = {
"exportAvg": True,
"exportDetails": True,
"exportConvergence": True,
"exportBoxplot": True,
}
run(optimizer, objectiveFuncs, NumOfRuns, params, exportFlags)
# Select optimizers
# "SSA","PSO","GA","BAT","FFA","GWO","WOA","MVO","MFO","CS"
optimizer = ["SSA", "PSO", "GA", "GWO"]
# Select objective function
# "SSE","TWCV","SC","DB","DI"
objectivefunc = ["SSE", "TWCV"]
# Select data sets
#"aggregation","aniso","appendicitis","balance","banknote","blobs","Blood","circles","diagnosis_II","ecoli","flame","glass","heart","ionosphere","iris","iris2D","jain","liver","moons","mouse","pathbased","seeds","smiley","sonar","varied","vary-density","vertebral2","vertebral3","wdbc","wine"
dataset_List = ["iris", "aggregation"]
# Select number of repetitions for each experiment.
# To obtain meaningful statistical results, usually 30 independent runs are executed for each algorithm.
NumOfRuns = 3
# Select general parameters for all optimizers (population size, number of iterations) ....
params = {'PopulationSize': 30, 'Iterations': 50}
#Choose whether to Export the results in different formats
export_flags = {
'Export_avg': True,
'Export_details': True,
'Export_details_labels': True,
'Export_convergence': True,
'Export_boxplot': True
}
run(optimizer, objectivefunc, dataset_List, NumOfRuns, params, export_flags)
# -*- coding: utf-8 -*-
"""
Created on Tue May 17 15:50:25 2016
@author: hossam
"""
from optimizer import run
# Select optimizers
# "SSA","PSO","GA","BAT","FFA","GWO","WOA","MVO","MFO","CS","HHO","SCA","JAYA","DE"
optimizer=["SSA","PSO","GWO"]
# Select benchmark function"
# "F1","F2","F3","F4","F5","F6","F7","F8","F9","F10","F11","F12","F13","F14","F15","F16","F17","F18","F19"
objectivefunc=["F3","F4"]
# Select number of repetitions for each experiment.
# To obtain meaningful statistical results, usually 30 independent runs are executed for each algorithm.
NumOfRuns=3
# Select general parameters for all optimizers (population size, number of iterations) ....
params = {'PopulationSize' : 30, 'Iterations' : 50}
#Choose whether to Export the results in different formats
export_flags = {'Export_avg':True, 'Export_details':True,
'Export_convergence':True, 'Export_boxplot':True}
run(optimizer, objectivefunc, NumOfRuns, params, export_flags)
# Select data sets
#"aggregation","aniso","appendicitis","balance","banknote","blobs","Blood","circles","diagnosis_II","ecoli","flame","glass","heart","ionosphere","iris","iris2D","jain","liver","moons","mouse","pathbased","seeds","smiley","sonar","varied","vary-density","vertebral2","vertebral3","wdbc","wine"
dataset_List = ["iris", "aggregation"]
# Select number of repetitions for each experiment.
# To obtain meaningful statistical results, usually 30 independent runs are executed for each algorithm.
NumOfRuns = 3
# Select general parameters for all optimizers (population size, number of iterations) ....
params = {'PopulationSize': 30, 'Iterations': 50}
#Choose whether to Export the results in different formats
export_flags = {
'Export_avg': True,
'Export_details': True,
'Export_details_labels': True,
'Export_convergence': True,
'Export_boxplot': True
}
run(optimizer,
objectivefunc,
dataset_List,
NumOfRuns,
params,
export_flags,
auto_cluster=False,
n_clusters=[3, 7],
labels_exist=True,
metric='cityblock')