Notebook

In [2]:

import nltk
nltk.download('stopwords')
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.linear_model import PassiveAggressiveClassifier
from sklearn.metrics import accuracy_score, confusion_matrix
from lightgbm import LGBMClassifier
from nltk.corpus import stopwords
from sklearn.ensemble import RandomForestClassifier
import pandas as pd
import numpy as np
import urllib3

[nltk_data] Downloading package stopwords to /root/nltk_data...
[nltk_data]   Package stopwords is already up-to-date!

Os dados utilizados de noticias são do remositório Fake.br-Corpus. São vários arquivos de texto com as notícias separados em diretórios diferentes, marcados como 'fake' e 'true' disponibilizados no GitHub. Exemplo do conteúdo de um arquivo:

In [3]:

http = urllib3.PoolManager() # PoolManager
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) # Desabilitando avisos
url = "https://raw.githubusercontent.com/roneysco/Fake.br-Corpus/master/full_texts/fake/%d.txt" % 1 # URL da notícia
r = http.request('GET', url) # Copiando notícia
print(r.data.decode('utf-8')) # Print com o texto decodificado

Kátia Abreu diz que vai colocar sua expulsão em uma moldura, mas não para de reclamar.	

A senadora Kátia Abreu (sem partido-TO) disse que sua expulsão do PMDB foi resultado de uma ação da cúpula atual da legenda que, segundo ela, é oportunista.

“Amanhã eu vou botar numa moldura dourada a minha expulsão, porque das mãos de onde veio, é um atestado de boa conduta para o meu currículo. Essas pessoas que me expulsaram não servem ao país. Eles se servem do país em seus benefícios próprios”, disse Kátia Abreu.

Ué, mas se a expulsão é algo tão bom para seu currículo, por que tanta choradeira, Kátia?

Sabemos o motivo. Provavelmente Kátia não tem valor para o PT, partido que já deveria tê-la absorvido. Ao que parece o PT gostava de Kátia somente se ela ficasse entrincheirada dentro do PMDB.

Ou seja, isso é se rebaixar demais. Resta a Kátia ficar chorando as pitangas por todos os cantos.

Em tempo: até o momento o PT não cadastrou Kátia Abreu em suas fileiras. Que situação patética para a ex-ministra da Agricultura de Dilma.

É criado um dataframe do pandas.

In [0]:

df = pd.DataFrame(columns = ['noticia', 'label'])

Adicionando as notícias ao dataframe (são 3600 notícias fake e 3600 notícias reais):

In [0]:

for i in range(1, 3601):
  url = "https://raw.githubusercontent.com/roneysco/Fake.br-Corpus/master/full_texts/fake/%d.txt" % i # URL da notícia
  r = http.request('GET', url) # Copiando notícia
  noticia = pd.DataFrame([[r.data.decode('utf-8'), 'fake']], columns = ['noticia', 'label'])
  df = df.append(noticia, ignore_index=True)

for i in range(1, 3601):
  url = "https://raw.githubusercontent.com/roneysco/Fake.br-Corpus/master/full_texts/true/%d.txt" % i # URL da notícia
  r = http.request('GET', url) # Copiando notícia
  noticia = pd.DataFrame([[r.data.decode('utf-8'), 'true']], columns = ['noticia', 'label'])
  df = df.append(noticia, ignore_index=True)

Início do data-frame

In [6]:

df.head()

Out[6]:

	noticia	label
0	Kátia Abreu diz que vai colocar sua expulsão e...	fake
1	Blog esquerdista dá a entender que reclamar de...	fake
2	Alckmin diz que por ele PSDB desembarca, mas...	fake
3	Cara de pau não tem limites: Zé Celso aciona M...	fake
4	Temer resolve o problema de Luislinda: liberd...	fake

Final do dataframe

In [7]:

df.tail()

Out[7]:

	noticia	label
7195	Ficou longe das notícias no fim de ano? Veja o...	true
7196	A nova denúncia contra o ex-presidente Luiz I...	true
7197	Como a Bahia virou uma potência mundial do mar...	true
7198	Alvo da Lava Jato, Bendine tinha passagem comp...	true
7199	Chefs convidados do Encontro Mundial das Cidad...	true

In [0]:

df2 = pd.read_csv('https://raw.githubusercontent.com/ViniciusNunes0/SIRENE-news/master/noticias-sirene.csv', sep=';')
df2 = df2[['noticia', 'classificacao']]
df2 = df2.rename(columns={"noticia": "noticia", "classificacao": "label"})
df2['label'] = df2['label'].replace({0: 'true', 1: 'fake'})
df2.head()
df = df.append(df2, ignore_index=True)

In [0]:

x_train,x_test,y_train,y_test=train_test_split(df['noticia'], df['label'], test_size=0.2, random_state=42)

In [0]:

tfidf_vectorizer = TfidfVectorizer(stop_words=stopwords.words('portuguese'),
                                analyzer='word',
                                ngram_range=(1, 1),
                                lowercase=True,
                                use_idf=True)

In [0]:

tfidf_train = tfidf_vectorizer.fit_transform(x_train) 
tfidf_test = tfidf_vectorizer.transform(x_test)

In [27]:

pac = PassiveAggressiveClassifier(max_iter=50, random_state=0)
pac.fit(tfidf_train,y_train)

y_pred = pac.predict(tfidf_test)
score = accuracy_score(y_test,y_pred)
print(f'Accuracy: {round(score*100,2)}%')

Accuracy: 96.69%

In [28]:

rf = RandomForestClassifier(random_state=0)
rf.fit(tfidf_train,y_train)

y_pred = rf.predict(tfidf_test)
score = accuracy_score(y_test,y_pred)
print(f'Accuracy: {round(score*100,2)}%')

Accuracy: 93.93%

In [41]:

lgbm = LGBMClassifier(learning_rate=0.1,
                      num_leaves=128,
                      min_child_samples=100,
                      ubsample=0.96,
                      colsample_bytree=0.28,
                      random_state=0,
                      subsample_freq=1,
                      n_estimators=100)
lgbm.fit(tfidf_train,y_train)

y_pred = lgbm.predict(tfidf_test)
score = accuracy_score(y_test,y_pred)
print(f'Accuracy: {round(score*100,2)}%')

Accuracy: 96.4%

In [30]:

!pip install scikit-optimize
from skopt import dummy_minimize

Collecting scikit-optimize
  Downloading https://files.pythonhosted.org/packages/4f/cf/b4aee828215a882495f7696ac85f8c1ecc0275923a18fecbb109ceaca651/scikit_optimize-0.7.2-py2.py3-none-any.whl (80kB)
     |████████████████████████████████| 81kB 2.5MB/s 
Requirement already satisfied: joblib in /usr/local/lib/python3.6/dist-packages (from scikit-optimize) (0.14.1)
Collecting pyaml
  Downloading https://files.pythonhosted.org/packages/35/1e/eda9fe07f752ced7afcef590e7d74390f0d9c9c0b7ff98317afbaa0697e3/pyaml-19.12.0-py2.py3-none-any.whl
Requirement already satisfied: scikit-learn>=0.19.1 in /usr/local/lib/python3.6/dist-packages (from scikit-optimize) (0.22.1)
Requirement already satisfied: scipy>=0.14.0 in /usr/local/lib/python3.6/dist-packages (from scikit-optimize) (1.4.1)
Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from scikit-optimize) (1.17.5)
Requirement already satisfied: PyYAML in /usr/local/lib/python3.6/dist-packages (from pyaml->scikit-optimize) (3.13)
Installing collected packages: pyaml, scikit-optimize
Successfully installed pyaml-19.12.0 scikit-optimize-0.7.2

In [0]:

def treinar_modelo(params):
    learning_rate = params[0]
    num_leaves = params[1]
    min_child_samples = params[2]
    subsample = params[3]
    colsample_bytree = params[4]
    
    print(params, '\n')
    
    mdl = LGBMClassifier(learning_rate=learning_rate,
                         num_leaves=num_leaves,
                         min_child_samples=min_child_samples,
                         subsample=subsample,
                         colsample_bytree=colsample_bytree,
                         random_state=0,
                         subsample_freq=1,
                         n_estimators=100)
    mdl.fit(tfidf_train,y_train)
    
    y_pred = mdl.predict(tfidf_test)
    
    return -accuracy_score(y_test,y_pred)

In [32]:

space = [(1e-3, 1e-1, 'log-uniform'), #learning rate
         (2, 128), # num_leaves
         (1, 100), # min_child_samples
         (0.05, 1.0), # subsample
         (0.1, 1.0)] # colsample bytree

resultado = dummy_minimize(treinar_modelo, space, random_state=1, verbose=1, n_calls=30)

Iteration No: 1 started. Evaluating function at random point.
[0.09871192514273254, 74, 10, 0.3372159440002478, 0.23208030173540176] 

Iteration No: 1 ended. Evaluation done at random point.
Time taken: 24.9603
Function value obtained: -0.9539
Current minimum: -0.9539
Iteration No: 2 started. Evaluating function at random point.
[0.001529949829431263, 78, 72, 0.3782826906908954, 0.457090726807603] 

Iteration No: 2 ended. Evaluation done at random point.
Time taken: 6.4905
Function value obtained: -0.9221
Current minimum: -0.9539
Iteration No: 3 started. Evaluating function at random point.
[0.01195730942971637, 128, 19, 0.5483207515942279, 0.49910760440160107] 

Iteration No: 3 ended. Evaluation done at random point.
Time taken: 37.0118
Function value obtained: -0.9338
Current minimum: -0.9539
Iteration No: 4 started. Evaluating function at random point.
[0.0028784217488024557, 16, 51, 0.9182639233502714, 0.5114843271882895] 

Iteration No: 4 ended. Evaluation done at random point.
Time taken: 9.7546
Function value obtained: -0.9183
Current minimum: -0.9539
Iteration No: 5 started. Evaluating function at random point.
[0.007267702383040958, 96, 97, 0.7894697745197069, 0.7443734643715278] 

Iteration No: 5 ended. Evaluation done at random point.
Time taken: 12.4704
Function value obtained: -0.9146
Current minimum: -0.9539
Iteration No: 6 started. Evaluating function at random point.
[0.04031948793713315, 63, 23, 0.5422449214947946, 0.8785182267810852] 

Iteration No: 6 ended. Evaluation done at random point.
Time taken: 33.8039
Function value obtained: -0.9481
Current minimum: -0.9539
Iteration No: 7 started. Evaluating function at random point.
[0.045529597892867466, 90, 14, 0.30939747550591, 0.15331888117140713] 

Iteration No: 7 ended. Evaluation done at random point.
Time taken: 16.3770
Function value obtained: -0.9430
Current minimum: -0.9539
Iteration No: 8 started. Evaluating function at random point.
[0.021930881089764206, 73, 4, 0.6880713925510277, 0.47060909107214777] 

Iteration No: 8 ended. Evaluation done at random point.
Time taken: 57.5811
Function value obtained: -0.9363
Current minimum: -0.9539
Iteration No: 9 started. Evaluating function at random point.
[0.002483715204721354, 26, 44, 0.7021758812975045, 0.8511631047076357] 

Iteration No: 9 ended. Evaluation done at random point.
Time taken: 14.2743
Function value obtained: -0.9091
Current minimum: -0.9539
Iteration No: 10 started. Evaluating function at random point.
[0.0010878688833867167, 43, 83, 0.98941803446117, 0.7733490889418555] 

Iteration No: 10 ended. Evaluation done at random point.
Time taken: 13.6617
Function value obtained: -0.9171
Current minimum: -0.9539
Iteration No: 11 started. Evaluating function at random point.
[0.003638211850540798, 89, 8, 0.14806470624875995, 0.5031041735583147] 

Iteration No: 11 ended. Evaluation done at random point.
Time taken: 24.5911
Function value obtained: -0.9255
Current minimum: -0.9539
Iteration No: 12 started. Evaluating function at random point.
[0.06564339077069616, 105, 24, 0.163515944581681, 0.572319439183401] 

Iteration No: 12 ended. Evaluation done at random point.
Time taken: 12.0019
Function value obtained: -0.9502
Current minimum: -0.9539
Iteration No: 13 started. Evaluating function at random point.
[0.0014697585967435188, 40, 9, 0.9149259627034465, 0.36903710098874454] 

Iteration No: 13 ended. Evaluation done at random point.
Time taken: 25.5028
Function value obtained: -0.9313
Current minimum: -0.9539
Iteration No: 14 started. Evaluating function at random point.
[0.014749532034944692, 89, 26, 0.633241401906253, 0.9608820910034701] 

Iteration No: 14 ended. Evaluation done at random point.
Time taken: 41.3526
Function value obtained: -0.9234
Current minimum: -0.9539
Iteration No: 15 started. Evaluating function at random point.
[0.0033262735259356143, 34, 89, 0.5567760660749166, 0.9549443246793757] 

Iteration No: 15 ended. Evaluation done at random point.
Time taken: 9.7227
Function value obtained: -0.8957
Current minimum: -0.9539
Iteration No: 16 started. Evaluating function at random point.
[0.009685436253688836, 2, 78, 0.09307844214592059, 0.225969507272543] 

Iteration No: 16 ended. Evaluation done at random point.
Time taken: 1.7682
Function value obtained: -0.8932
Current minimum: -0.9539
Iteration No: 17 started. Evaluating function at random point.
[0.03844210597293627, 93, 22, 0.8889692020284521, 0.5867093706408683] 

Iteration No: 17 ended. Evaluation done at random point.
Time taken: 42.2379
Function value obtained: -0.9435
Current minimum: -0.9539
Iteration No: 18 started. Evaluating function at random point.
[0.00786973960931508, 45, 21, 0.40870512409353993, 0.5845822248519866] 

Iteration No: 18 ended. Evaluation done at random point.
Time taken: 17.2985
Function value obtained: -0.9284
Current minimum: -0.9539
Iteration No: 19 started. Evaluating function at random point.
[0.020164978538544195, 59, 83, 0.6559446598566927, 0.2136833965403995] 

Iteration No: 19 ended. Evaluation done at random point.
Time taken: 7.6264
Function value obtained: -0.9317
Current minimum: -0.9539
Iteration No: 20 started. Evaluating function at random point.
[0.024010940718920456, 9, 25, 0.3814534248789504, 0.3429351025885235] 

Iteration No: 20 ended. Evaluation done at random point.
Time taken: 6.8313
Function value obtained: -0.9246
Current minimum: -0.9539
Iteration No: 21 started. Evaluating function at random point.
[0.061911658253265375, 96, 61, 0.9665980447909663, 0.6970973480366033] 

Iteration No: 21 ended. Evaluation done at random point.
Time taken: 28.6212
Function value obtained: -0.9523
Current minimum: -0.9539
Iteration No: 22 started. Evaluating function at random point.
[0.01751424579956557, 110, 93, 0.9520147957717178, 0.5049209201319466] 

Iteration No: 22 ended. Evaluation done at random point.
Time taken: 13.6599
Function value obtained: -0.9292
Current minimum: -0.9539
Iteration No: 23 started. Evaluating function at random point.
[0.014347598955915168, 84, 87, 0.27517563123087635, 0.9130415685060285] 

Iteration No: 23 ended. Evaluation done at random point.
Time taken: 5.5491
Function value obtained: -0.9116
Current minimum: -0.9539
Iteration No: 24 started. Evaluating function at random point.
[0.014039737029591284, 17, 6, 0.6362876679396877, 0.3939804115948866] 

Iteration No: 24 ended. Evaluation done at random point.
Time taken: 17.6811
Function value obtained: -0.9309
Current minimum: -0.9539
Iteration No: 25 started. Evaluating function at random point.
[0.011327034010293172, 103, 14, 0.3894062720023748, 0.9176816358278194] 

Iteration No: 25 ended. Evaluation done at random point.
Time taken: 47.1847
Function value obtained: -0.9250
Current minimum: -0.9539
Iteration No: 26 started. Evaluating function at random point.
[0.017649005221070314, 98, 56, 0.9329653720565734, 0.7218072257652316] 

Iteration No: 26 ended. Evaluation done at random point.
Time taken: 27.0328
Function value obtained: -0.9259
Current minimum: -0.9539
Iteration No: 27 started. Evaluating function at random point.
[0.09877469581360704, 123, 84, 0.18027896214743389, 0.9393359167334473] 

Iteration No: 27 ended. Evaluation done at random point.
Time taken: 4.9769
Function value obtained: -0.9477
Current minimum: -0.9539
Iteration No: 28 started. Evaluating function at random point.
[0.024753483395116363, 45, 7, 0.7676898999723432, 0.7784885696151218] 

Iteration No: 28 ended. Evaluation done at random point.
Time taken: 46.1493
Function value obtained: -0.9313
Current minimum: -0.9539
Iteration No: 29 started. Evaluating function at random point.
[0.07015345605895347, 11, 67, 0.16805741387355647, 0.11789212045581604] 

Iteration No: 29 ended. Evaluation done at random point.
Time taken: 2.7115
Function value obtained: -0.9330
Current minimum: -0.9539
Iteration No: 30 started. Evaluating function at random point.
[0.0011282932078263237, 23, 41, 0.28390051422289364, 0.8740251538145993] 

Iteration No: 30 ended. Evaluation done at random point.
Time taken: 9.1497
Function value obtained: -0.9079
Current minimum: -0.9539

In [35]:

resultado.x

Out[35]:

[0.09871192514273254, 74, 10, 0.3372159440002478, 0.23208030173540176]

In [0]:

from skopt import gp_minimize

In [37]:

resultados_gp = gp_minimize(treinar_modelo, space, random_state=1, verbose=1, n_calls=50, n_random_starts=10)

Iteration No: 1 started. Evaluating function at random point.
[0.09871192514273254, 120, 14, 0.9990884895579377, 0.3124800792567785] 

Iteration No: 1 ended. Evaluation done at random point.
Time taken: 49.8891
Function value obtained: -0.9598
Current minimum: -0.9598
Iteration No: 2 started. Evaluating function at random point.
[0.006210998932353835, 51, 67, 0.9387621172657304, 0.8616798250174156] 

Iteration No: 2 ended. Evaluation done at random point.
Time taken: 17.2649
Function value obtained: -0.9121
Current minimum: -0.9598
Iteration No: 3 started. Evaluating function at random point.
[0.004232013397179603, 68, 45, 0.2680983530433343, 0.5809725180523154] 

Iteration No: 3 ended. Evaluation done at random point.
Time taken: 8.6664
Function value obtained: -0.9200
Current minimum: -0.9598
Iteration No: 4 started. Evaluating function at random point.
[0.0672858974212934, 60, 44, 0.9421713999524447, 0.8005503127028804] 

Iteration No: 4 ended. Evaluation done at random point.
Time taken: 32.4960
Function value obtained: -0.9556
Current minimum: -0.9598
Iteration No: 5 started. Evaluating function at random point.
[0.027035912483147396, 103, 10, 0.5422449214947946, 0.8785182267810853] 

Iteration No: 5 ended. Evaluation done at random point.
Time taken: 62.7098
Function value obtained: -0.9397
Current minimum: -0.9598
Iteration No: 6 started. Evaluating function at random point.
[0.045529597892867466, 107, 28, 0.1062810412364853, 0.7034752360620511] 

Iteration No: 6 ended. Evaluation done at random point.
Time taken: 7.4884
Function value obtained: -0.9401
Current minimum: -0.9598
Iteration No: 7 started. Evaluating function at random point.
[0.01535080081765723, 87, 42, 0.23767335308554222, 0.3606666764912312] 

Iteration No: 7 ended. Evaluation done at random point.
Time taken: 7.3549
Function value obtained: -0.9276
Current minimum: -0.9598
Iteration No: 8 started. Evaluating function at random point.
[0.0019241559628256106, 101, 42, 0.0824627456265471, 0.661626987829618] 

Iteration No: 8 ended. Evaluation done at random point.
Time taken: 4.0012
Function value obtained: -0.9008
Current minimum: -0.9598
Iteration No: 9 started. Evaluating function at random point.
[0.02095421812724112, 40, 45, 0.2610183201586061, 0.16602775456833962] 

Iteration No: 9 ended. Evaluation done at random point.
Time taken: 5.6642
Function value obtained: -0.9284
Current minimum: -0.9598
Iteration No: 10 started. Evaluating function at random point.
[0.008679147174590262, 14, 90, 0.163515944581681, 0.5723194391834011] 

Iteration No: 10 ended. Evaluation done at random point.
Time taken: 3.3876
Function value obtained: -0.9049
Current minimum: -0.9598
Iteration No: 11 started. Searching for the next optimal point.
[0.1, 2, 1, 1.0, 0.1] 

Iteration No: 11 ended. Search finished for the next optimal point.
Time taken: 8.1544
Function value obtained: -0.9204
Current minimum: -0.9598
Iteration No: 12 started. Searching for the next optimal point.
[0.1, 82, 100, 1.0, 0.1] 

Iteration No: 12 ended. Search finished for the next optimal point.
Time taken: 9.7585
Function value obtained: -0.9573
Current minimum: -0.9598
Iteration No: 13 started. Searching for the next optimal point.
[0.1, 128, 100, 1.0, 1.0] 

Iteration No: 13 ended. Search finished for the next optimal point.
Time taken: 26.9558
Function value obtained: -0.9598
Current minimum: -0.9598
Iteration No: 14 started. Searching for the next optimal point.
[0.1, 87, 1, 0.05, 1.0] 

Iteration No: 14 ended. Search finished for the next optimal point.
Time taken: 69.4241
Function value obtained: -0.7647
Current minimum: -0.9598
Iteration No: 15 started. Searching for the next optimal point.
[0.1, 128, 17, 0.6791405330341167, 0.36978260724986156] 

Iteration No: 15 ended. Search finished for the next optimal point.
Time taken: 47.4743
Function value obtained: -0.9581
Current minimum: -0.9598
Iteration No: 16 started. Searching for the next optimal point.
[0.1, 128, 100, 0.9562060254291818, 0.2826514395863122] 

Iteration No: 16 ended. Search finished for the next optimal point.
Time taken: 13.6883
Function value obtained: -0.9619
Current minimum: -0.9619
Iteration No: 17 started. Searching for the next optimal point.
[0.1, 128, 16, 0.7170517565581257, 0.7192043907505543] 

Iteration No: 17 ended. Search finished for the next optimal point.
Time taken: 69.0674
Function value obtained: -0.9552
Current minimum: -0.9619
Iteration No: 18 started. Searching for the next optimal point.
[0.001, 2, 18, 1.0, 0.1] 

Iteration No: 18 ended. Search finished for the next optimal point.
Time taken: 3.5221
Function value obtained: -0.9091
Current minimum: -0.9619
Iteration No: 19 started. Searching for the next optimal point.
[0.001, 128, 100, 0.6126979403477888, 1.0] 

Iteration No: 19 ended. Search finished for the next optimal point.
Time taken: 11.6402
Function value obtained: -0.8819
Current minimum: -0.9619
Iteration No: 20 started. Searching for the next optimal point.
[0.029872145925565766, 2, 24, 0.804947178555389, 0.1] 

Iteration No: 20 ended. Search finished for the next optimal point.
Time taken: 3.4398
Function value obtained: -0.9079
Current minimum: -0.9619
Iteration No: 21 started. Searching for the next optimal point.
[0.1, 128, 4, 0.05, 0.1] 

Iteration No: 21 ended. Search finished for the next optimal point.
Time taken: 13.1276
Function value obtained: -0.7186
Current minimum: -0.9619
Iteration No: 22 started. Searching for the next optimal point.
[0.1, 46, 69, 0.05, 0.27886906080963625] 

Iteration No: 22 ended. Search finished for the next optimal point.
Time taken: 2.7451
Function value obtained: -0.9259
Current minimum: -0.9619
Iteration No: 23 started. Searching for the next optimal point.
[0.1, 128, 10, 0.9667024841699353, 0.6580246295842597] 

Iteration No: 23 ended. Search finished for the next optimal point.
Time taken: 86.3331
Function value obtained: -0.9527
Current minimum: -0.9619
Iteration No: 24 started. Searching for the next optimal point.
[0.1, 128, 85, 1.0, 1.0] 

Iteration No: 24 ended. Search finished for the next optimal point.
Time taken: 31.6482
Function value obtained: -0.9577
Current minimum: -0.9619
Iteration No: 25 started. Searching for the next optimal point.
[0.1, 128, 29, 0.47229873092084085, 1.0] 

Iteration No: 25 ended. Search finished for the next optimal point.
Time taken: 49.9670
Function value obtained: -0.9573
Current minimum: -0.9619
Iteration No: 26 started. Searching for the next optimal point.
[0.001, 128, 36, 1.0, 0.1] 

Iteration No: 26 ended. Search finished for the next optimal point.
Time taken: 19.9594
Function value obtained: -0.9188
Current minimum: -0.9619
Iteration No: 27 started. Searching for the next optimal point.
[0.1, 128, 47, 1.0, 1.0] 

Iteration No: 27 ended. Search finished for the next optimal point.
Time taken: 52.3109
Function value obtained: -0.9598
Current minimum: -0.9619
Iteration No: 28 started. Searching for the next optimal point.
[0.1, 128, 51, 0.690163518775476, 0.1] 

Iteration No: 28 ended. Search finished for the next optimal point.
Time taken: 15.3943
Function value obtained: -0.9573
Current minimum: -0.9619
Iteration No: 29 started. Searching for the next optimal point.
[0.1, 128, 78, 0.5821641489959132, 0.1] 

Iteration No: 29 ended. Search finished for the next optimal point.
Time taken: 8.3819
Function value obtained: -0.9539
Current minimum: -0.9619
Iteration No: 30 started. Searching for the next optimal point.
[0.1, 128, 61, 0.46493671909185036, 1.0] 

Iteration No: 30 ended. Search finished for the next optimal point.
Time taken: 21.6823
Function value obtained: -0.9548
Current minimum: -0.9619
Iteration No: 31 started. Searching for the next optimal point.
[0.07065505099416787, 94, 21, 0.6579886820786071, 1.0] 

Iteration No: 31 ended. Search finished for the next optimal point.
Time taken: 59.9456
Function value obtained: -0.9548
Current minimum: -0.9619
Iteration No: 32 started. Searching for the next optimal point.
[0.1, 128, 91, 1.0, 0.1] 

Iteration No: 32 ended. Search finished for the next optimal point.
Time taken: 11.7756
Function value obtained: -0.9581
Current minimum: -0.9619
Iteration No: 33 started. Searching for the next optimal point.
[0.1, 128, 47, 0.694258025221401, 1.0] 

Iteration No: 33 ended. Search finished for the next optimal point.
Time taken: 42.6876
Function value obtained: -0.9611
Current minimum: -0.9619
Iteration No: 34 started. Searching for the next optimal point.
[0.001, 74, 100, 0.6290011906343209, 0.6851071876283265] 

Iteration No: 34 ended. Search finished for the next optimal point.
Time taken: 9.7367
Function value obtained: -0.9129
Current minimum: -0.9619
Iteration No: 35 started. Searching for the next optimal point.
[0.1, 2, 100, 0.6882574895687902, 1.0] 

Iteration No: 35 ended. Search finished for the next optimal point.
Time taken: 3.6897
Function value obtained: -0.9154
Current minimum: -0.9619
Iteration No: 36 started. Searching for the next optimal point.
[0.001, 104, 1, 1.0, 0.1] 

Iteration No: 36 ended. Search finished for the next optimal point.
Time taken: 61.9762
Function value obtained: -0.9112
Current minimum: -0.9619
Iteration No: 37 started. Searching for the next optimal point.
[0.1, 2, 94, 1.0, 0.7579423824962375] 

Iteration No: 37 ended. Search finished for the next optimal point.
Time taken: 3.4479
Function value obtained: -0.9158
Current minimum: -0.9619
Iteration No: 38 started. Searching for the next optimal point.
[0.001, 2, 22, 0.05, 1.0] 

Iteration No: 38 ended. Search finished for the next optimal point.
Time taken: 4.0558
Function value obtained: -0.7961
Current minimum: -0.9619
Iteration No: 39 started. Searching for the next optimal point.
[0.1, 128, 100, 0.2872896736759894, 0.6469028700861311] 

Iteration No: 39 ended. Search finished for the next optimal point.
Time taken: 6.1838
Function value obtained: -0.9489
Current minimum: -0.9619
Iteration No: 40 started. Searching for the next optimal point.
[0.1, 29, 100, 0.35649852215840644, 0.32166956996010443] 

Iteration No: 40 ended. Search finished for the next optimal point.
Time taken: 6.0237
Function value obtained: -0.9539
Current minimum: -0.9619
Iteration No: 41 started. Searching for the next optimal point.
[0.1, 64, 100, 0.7550429345651503, 0.5484507122183814] 

Iteration No: 41 ended. Search finished for the next optimal point.
Time taken: 14.4771
Function value obtained: -0.9585
Current minimum: -0.9619
Iteration No: 42 started. Searching for the next optimal point.
[0.1, 94, 100, 0.6230200199744601, 0.2416758362492999] 

Iteration No: 42 ended. Search finished for the next optimal point.
Time taken: 8.5844
Function value obtained: -0.9539
Current minimum: -0.9619
Iteration No: 43 started. Searching for the next optimal point.
[0.1, 85, 1, 0.8192871244331369, 0.7900859342771712] 

Iteration No: 43 ended. Search finished for the next optimal point.
Time taken: 177.0017
Function value obtained: -0.9552
Current minimum: -0.9619
Iteration No: 44 started. Searching for the next optimal point.
[0.1, 2, 1, 0.13948477404147397, 0.32121755739313207] 

Iteration No: 44 ended. Search finished for the next optimal point.
Time taken: 9.0142
Function value obtained: -0.9158
Current minimum: -0.9619
Iteration No: 45 started. Searching for the next optimal point.
[0.1, 68, 100, 0.4328201718060503, 0.45193645904272195] 

Iteration No: 45 ended. Search finished for the next optimal point.
Time taken: 7.8458
Function value obtained: -0.9518
Current minimum: -0.9619
Iteration No: 46 started. Searching for the next optimal point.
[0.1, 77, 10, 0.7664855205658347, 0.1] 

Iteration No: 46 ended. Search finished for the next optimal point.
Time taken: 26.3770
Function value obtained: -0.9535
Current minimum: -0.9619
Iteration No: 47 started. Searching for the next optimal point.
[0.0824998168892209, 7, 100, 0.10888942866593732, 1.0] 

Iteration No: 47 ended. Search finished for the next optimal point.
Time taken: 3.5684
Function value obtained: -0.9330
Current minimum: -0.9619
Iteration No: 48 started. Searching for the next optimal point.
[0.03908723990709154, 110, 100, 0.23667895805629796, 0.9426636175495662] 

Iteration No: 48 ended. Search finished for the next optimal point.
Time taken: 5.3322
Function value obtained: -0.9288
Current minimum: -0.9619
Iteration No: 49 started. Searching for the next optimal point.
[0.024294875676627584, 128, 100, 1.0, 1.0] 

Iteration No: 49 ended. Search finished for the next optimal point.
Time taken: 20.1392
Function value obtained: -0.9271
Current minimum: -0.9619
Iteration No: 50 started. Searching for the next optimal point.
[0.1, 128, 31, 0.9623256999582401, 1.0] 

Iteration No: 50 ended. Search finished for the next optimal point.
Time taken: 65.2303
Function value obtained: -0.9569
Current minimum: -0.9619

In [39]:

resultados_gp.x

Out[39]:

[0.1, 128, 100, 0.9562060254291818, 0.2826514395863122]

In [0]:

[0.1, 23, 51, 0.8039348617451548, 0.34702698317511055] 