import statsmodels.api as sm from sklearn.datasets import fetch_openml import pandas as pd # Load the Boston housing dataset from OpenML boston = fetch_openml(name='boston', version=1) boston_df = pd.DataFrame(boston.data, columns=boston.feature_names) boston_df['PRICE'] = boston.target...
我正在尝试在 Python 中加载 MNIST 原始数据集。 sklearn.datasets.fetch_openml 函数似乎对此不起作用。
from sklearn.datasets import fetch_openml from sklearn.svm import SVC mnist = fetch_openml('mnist_784', version=1, as_frame=False) # 默认返回Pandas的DF类型 # sklearn加载的数据集类似字典结构 from sklearn.preprocessing import StandardScaler X, y = mnist["data"], mnist["target"] stder =...
首先,我们需要导入相关的库并加载数据集: importnumpyasnpimportmatplotlib.pyplotaspltfromsklearn.datasetsimportfetch_openmlfromsklearn.model_selectionimporttrain_test_splitfromsklearn.preprocessingimportStandardScaler# 加载数据集mnist=fetch_openml('mnist_784')X,y=mnist['data'],mnist['target']# 数据分割X...
from sklearn.datasets import fetch_openml from sklearn.preprocessing import RobustScaler import matplotlib.pyplot as plt import seaborn as sns from pyod.models.iforest import IForest from pyod.models.lof import LOF from pyod.models.ecod import ECOD ...
importnumpyasnpimportpandasaspdfromsklearn.datasetsimportfetch_openmlimportmatplotlib.pyplotasplt# 加载MNIST数据集mnist=fetch_openml('mnist_784',version=1)# 特征和标签X,y=mnist['data'],mnist['target'] 1. 2. 3. 4. 5. 6. 7. 8.
import copy import numpy as np import pandas as pd from sklearn.compose import ColumnTransformer from sklearn.datasets import fetch_openml from sklearn.impute import SimpleImputer from sklearn.linear_model import LogisticRegression from sklearn.model_selection import train_test_split from sklearn.prepr...
# Load the Boston housing dataset from OpenMLboston = fetch_openml(name='boston', version=1)boston_df = pd.DataFrame(boston.data, columns=boston.feature_names)boston_df['PRICE'] = boston.target # Display the first few rows of the dataframeprint(boston_df.head()) ...
import copy import numpy as np import pandas as pd from sklearn.compose import ColumnTransformer from sklearn.datasets import fetch_openml from sklearn.impute import SimpleImputer from sklearn.linear_model import LogisticRegression from sklearn.model_selection import train_test_split from sklearn.prepr...
import numpy as np import matplotlib import matplotlib.pyplot as plt from sklearn.datasets import fetch_openml 导入数据集 mnist = fetch_openml('mnist_784') 导入数据X,y X = mnist['data'] y = mnist['target'] 这个数据集帮你分好类了,不用进行train_test_split的分割 X_train = np...