# -*- coding: utf-8 -*-
"""
Created on Mon Mar 6 15:51:35 2017
@author: Alon
"""
import nnDNA as dna
import geneticLib.Evolution as Evo
import basicLib.loadAndTest as orig
users = orig.loadAndUpdateFeatures(
'../input/users_2014_actions_combined_device.csv')
args = {'users': users}
dnaArg = {'dna': dna, 'args': args}
Ev = Evo.Evolution(dnaArg,
usePrints=True,
populationSize=6,
numOfEvolutionSteps=10,
mutationFactor=0.1)
Ev.run()
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 1 13:41:01 2017
@author: Alon
"""
import featureDNA as dna
import geneticLib.Evolution as Evo
Ev = Evo.Evolution(dna,
usePrints=True,
populationSize=15,
numOfEvolutionSteps=10)
Ev.run()
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 1 13:41:01 2017
@author: Alon
"""
import featureDNA as dna
import geneticLib.Evolution as Evo
import basicLib.loadAndTest as orig
users = orig.loadAndUpdateFeatures('../input/users_2014_sessions_norm.csv')
args = {'users': users}
dnaArg = {'dna': dna, 'args': args}
Ev = Evo.Evolution(dnaArg,
usePrints=True,
populationSize=60,
numOfEvolutionSteps=15)
Ev.run()
"""
import featureDNA as dna
import geneticLib.Evolution as Evo
import basicLib.loadAndTest as orig
from sklearn import tree
predictMethod = tree.DecisionTreeClassifier()
users = orig.loadAndUpdateFeatures('../input/users_2014_sessions_norm.csv')
args = {'users': users, 'predictMethod': predictMethod}
dnaArg = {'dna': dna, 'args': args}
features1 = [
'action_toggle_archived_thread_##_click_##_toggle_archived_thread'
]
features2 = [
'affiliate_provider', 'first_affiliate_tracked', 'first_browser',
'first_device_type', 'gender', 'language', 'signup_app', 'signup_method',
'signup_flow'
]
genesList = [features1, features2]
hotStart = {
'numOfGenes': len(genesList),
'genesList': genesList
} # genes is a list of list (list of list of feturs)
Ev = Evo.Evolution(dnaArg,
usePrints=True,
populationSize=20,
numOfEvolutionSteps=60,
hotStart=hotStart)
Ev.run()
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 6 15:51:35 2017
@author: Alon
"""
import nnDNA as dna
import geneticLib.Evolution as Evo
import basicLib.loadAndTest as orig
import pandas as pd
users, yRes = orig.loadAndUpdateFeatures('../input/train_users.csv')
users = pd.concat([users, yRes], axis=1)
args = {'users': users}
dnaArg = {'dna': dna, 'args': args}
Ev = Evo.Evolution(dnaArg,
usePrints=True,
populationSize=20,
numOfEvolutionSteps=60,
mutationFactor=0.1,
bestMovesOn=2)
Ev.run()