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import matplotlib.pyplot as plt | |
import pandas as pd | |
for i in range(50): | |
print(i) |
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# bibliotecas | |
from sklearn.datasets import load_iris | |
from sklearn.model_selection import train_test_split | |
from sklearn.neighbors import KNeighborsClassifier | |
from sklearn.preprocessing import Normalizer | |
import numpy as np | |
# remove warnings | |
import warnings | |
warnings.filterwarnings("ignore") |
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# bibliotecas | |
from sklearn.datasets import load_iris | |
from sklearn.model_selection import train_test_split | |
from sklearn.neighbors import KNeighborsClassifier | |
from sklearn.preprocessing import Normalizer | |
import numpy as np | |
# remove warnings | |
import warnings | |
warnings.filterwarnings("ignore") |
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# bibliotecas | |
from sklearn.datasets import load_iris | |
from sklearn.model_selection import train_test_split | |
from sklearn.neighbors import KNeighborsClassifier | |
import numpy as np | |
# remove warnings | |
import warnings | |
warnings.filterwarnings("ignore") |
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# bibliotecas | |
from sklearn.datasets import load_iris | |
import pandas as pd | |
import matplotlib.pyplot as plt | |
import seaborn as sns | |
# dataset | |
iris = load_iris() | |
# dataset to pandas dataframe |
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# bibliotecas | |
from sklearn.datasets import load_iris | |
from sklearn.model_selection import train_test_split | |
from sklearn.neighbors import KNeighborsClassifier | |
from sklearn.metrics import classification_report | |
# remove warnings | |
import warnings | |
warnings.filterwarnings("ignore") |
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# bibliotecas | |
from sklearn.datasets import load_iris | |
from sklearn.model_selection import train_test_split | |
from sklearn.neighbors import KNeighborsClassifier | |
import numpy as np | |
# remove warnings | |
import warnings | |
warnings.filterwarnings("ignore") |
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# bibliotecas | |
from sklearn.datasets import load_iris | |
from sklearn.model_selection import train_test_split | |
from sklearn.neighbors import KNeighborsClassifier | |
# dataset | |
iris = load_iris() | |
# features e target | |
X = iris.data |
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print("Hello, world!") |