拼写错误，首行导入时把导入的包重命名为detasets，而第三行使用时缺写成datasets，首行拼写错误，应写为dataset
如果load_iris是自定义函数: 确保你已经在代码中正确定义了load_iris函数。如果这是你的自定义函数,检查你的代码库,确保在调用load_iris之前,该函数已经被定义。 示例(如果load_iris是自定义的): python def load_iris(): # 自定义加载鸢尾花数据集的逻辑 pass data = load_iris() 如果load_iris来自外部...
May I know how to correct the NameError: name 'xx' is not defined ? Code: import numpy as np import matplotlib.pyplot as plt from sklearn import svm, datasets # import some data to play with iris = datasets.load_iris() X = iris.data[:,[2,3]] y = iris.target def plotSVC(titl...
File "pca_iris.py", line 12, in <module> X = StandardScaler().fit_transform(X) NameError: name 'StandardScaler' is not defined I searched this web and saw similar topics, however, the version is correct and I don't know what to do further. The line import sklearn is at the top ...
NameError: name 'x' is not defined 是 Python 中常见的错误之一,通常表示你尝试访问一个尚未定义的变量或函数。...特别是全局名称未定义时,意味着你在使用某个全局变量或函数时,Python 在当前命名空间中找不到该名称。...1、问题背景在使用 Python 时,如果遇到了 NameError: global name 'control_queue' ...
Error: object 'y' not found Here’s an example of this error in the wild…. see the code below… # Attempt to access an object that doesn't exist my_data <- iris head(my_data) tail(my_data2) Since my_data2 hasn’t been defined in the program (and allocated within memory), R...
fromsklearn.model_selectionimporttrain_test_splitfromsklearn.datasetsimportload_iris# 加载鸢尾花数据集data=load_iris()X,y=data.data,data.target# 使用train_test_split函数划分数据集X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3,random_state=42)# 对训练集和测试集进行前向...
开发者ID:scollis,项目名称:iris,代码行数:56,代码来源:calculus.py 示例4: _get_xy_dim_coords ▲点赞 1▼ def_get_xy_dim_coords(cube):""" Return the x and y dimension coordinates from a cube. This function raises a ValueError if the cube does not contain one and ...
ERROR Running examples in‘test-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: mutate_cond > ### Title: Conditional mutate > ### Aliases: mutate_cond > > ### ** Examples > > data(iris)...
tf.float32.as_datatype_enum) tflite_model=tf.contrib.lite.toco_convert(sess.graph_def,[x],[mxc]) open("wow.tflite","w").write(tflite_model) #IRIS.DATA is this: 5.1,3.5,1.4,0.2,Iris-setosa 4.9,3.0,1.4,0.2,Iris-setosa 4.7,3.2,1.3,0.2,Iris-setosa ...