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from sklearn import datasets
import numpy as np
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.linear_model import Perceptron
from sklearn.metrics import accuracy_score

# Irisデータセットをロード
iris = datasets.load_iris()
# 3,4列目の特徴量を抽出

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import pandas as pd

df = pd.read_csv('https://archive.ics.uci.edu/ml/'
        'machine-learning-databases/iris/iris.data', header=None)
import matplotlib.pyplot as plt
import numpy as np

y = df.iloc[0:100, 4].values
y = np.where(y == 'Iris-setosa', -1, 1)
X = df.iloc[0:100, [0, 2]].values

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import numpy as np

class Perceptron(object):
    """
    eta: 学習率(0.0<eta<1.0)
    n_iter: トレーニング回数
    """
    def __init__(self, eta=0.01, n_iter=10):
        self.eta = eta
        self.n_iter = n_iter