机器学习-感知机(Perceptron)-Scikit-Learn

最新推荐文章于 2024-08-30 08:33:07 发布

Santorinisu

最新推荐文章于 2024-08-30 08:33:07 发布

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Section I: Load package

#Section 1: Load package
from sklearn import datasets
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.linear_model import Perceptron
from sklearn.metrics import accuracy_score

plt.rcParams['figure.dpi']=200
plt.rcParams['savefig.dpi']=200
font = {
   'family': 'Times New Roman',
        'weight': 'light'}
plt.rc("font", **font)

Section II: Load data and split them into train/test dataset

#Section 2: Load data and split it into train/test dataset
iris=datasets.load_iris()
X=iris.data[:,[2,3]]
y=iris.target

X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3,random_state=1,stratify=y)
print('Label counts in y:',np.bincount(y))