pip install scikit-learn 1. 能够成功运行以下代码表示安装成功: import numpy as np import matplotlib.pyplot as plt from sklearn.datasets import make_blobs from sklearn.discriminant_analysis import LinearDiscriminantAnalysis n_train = 20 # samples for training n_test = 200 # samples for testing n_...
bfloat16).cuda() input_text = """#utils.py import torch from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.metrics import accuracy_score def load_data(): iris = datasets.load_iris() X = iris.data ...
from sklearn import preprocessing;enc = preprocessing.OneHotEncoder();enc.fit([[0, 0, 3], [1, 1, 0], [0, 2, 1], [1, 0, 2]]) # fit来学习编码 ;enc.transform([[0, 1, 3]]).toarray() # 把所有列分别转化成one-hot,比如第2列总共可以取0/1/2,所以把1编码为one-hot形式,如...
bfloat16).cuda() input_text = """#utils.py import torch from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.metrics import accuracy_score def load_data(): iris = datasets.load_iris() X = iris.data ...
def init(): model_path = Model.get_model_path( model_name="sklearn_regression_model.pkl") model = joblib.load(model_path) Once the init function has been created, replace all the code under the heading "Load Model" with a single call to init as follows: Python Copy init() In ...
def init(): model_path = Model.get_model_path( model_name="sklearn_regression_model.pkl") model = joblib.load(model_path) Once the init function has been created, replace all the code under the heading "Load Model" with a single call to init as follows: Python Copy init() In ...
from sklearn.preprocessing import LabelEncoder sex_labels = gle.transform(df_test['Sex']) df_test['Sex_labelencoder'] = sex_labels df_test.head() 二、如果我们想处理这类变量,达到下面的效果: 1)用pandas 自带的 pd.get.dummies() # Sex ...
brew cask install visual-studio-code 当然也可以选择不自动安装已有扩展,同样可以顺利进行后面的配置。 ? What type of extension do you want to create? New Extension Pack ? Add the currently installed extensions to the extension pack? No ? What's the name of your extension? vscode-java-dev-tools...
开发机的链接命令可以在开发机控制台对应开发机"SSH连接"找到,复制登录命令到vscode的弹窗中然后回车,vscode就会开始链接InternStudio的服务器,记得此时切回去复制一下ssh的密码,待会会用到。 在新的弹窗中将ssh密码粘贴进去然后回车。随后会弹窗让选择远程终端的类型,这边我们的开发机是linux系统,所以选择linux就好。
# Function performing linear regression on diabetes dataset def regression(): import numpy as np from sklearn import datasets, linear_model from sklearn.metrics import mean_squared_error, r2_score # Load the diabetes dataset diabetes_X, diabetes_y = datasets.load_diabetes(return_X_y=True) # ...