小编har*_*shi的帖子

我是这个机器学习的新手，并使用这个波士顿数据集进行预测。除了precision_score 和accuracy_score 的结果外，一切都工作正常。这就是我所做的：

import pandas as pd 
import sklearn 
from sklearn.linear_model import LinearRegression
from sklearn import preprocessing,cross_validation, svm
from sklearn.datasets import load_boston
import numpy as np
from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score, classification_report, confusion_matrix

boston = load_boston()
df = pd.DataFrame(boston.data)
df.columns= boston.feature_names
df['Price']= boston.target

X = np.array(df.drop(['Price'],axis=1), dtype=np.float64)
X = preprocessing.scale(X)

y = np.array(df['Price'], dtype=np.float64)

print (len(X[:,6:7]),len(y))

X_train,X_test,y_train,y_test=cross_validation.train_test_split(X,y,test_size=0.30)

clf =LinearRegression()
clf.fit(X_train,y_train)
y_predict = clf.predict(X_test)

print(y_predict,len(y_predict))
print (accuracy_score(y_test, y_predict))
print(precision_score(y_test, y_predict,average = 'macro'))

现在我收到以下错误：

文件“LinearRegression.py”，第 33 行，在

 accuracy = accuracy_score(y_test, …

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我对 dash 还很陌生，并试图将两个下拉菜单并排放置，但它们似乎根本不起作用，而是彼此位于下方。我想我搞砸了 HTML div 的“className”排列。代码如下：

app.layout = html.Div([

html.Div( [

    html.H1("Web Application Dashboards with Dash", style={'text-align': 'center'}),

 ] ),

html.Div(
className = "row",children =[
    html.Div(className='six columns', children=[
        dcc.Dropdown(
            id='dropdown_dataset',
                    options=[
                        {'label': 'diabetes', 'value': 'diabetes'},
                        {'label': 'Custom Data', 'value': 'custom'},
                        {'label': 'Linear Curve', 'value': 'linear'},
                    ],
                    value='diabetes',
                    clearable=False,
                    searchable=False,
        )])
    ,html.Div(className='six columns', children=[
        dcc.Dropdown(
        id='dropdown_dataset_2',
        options=[
            {'label': 'sinh', 'value': 'sinh'},
            {'label': 'tanh', 'value': 'cosh'},
        ],
        value='diabetes',[![enter image description here][1]][1]
        clearable=False,
        searchable=False,
    )])
  ])
  ])



  if __name__ == '__main__':
        app.run_server(host='127.0.0.1',port = …

正则化是归一化的子集吗？我知道当所有值都不在同一范围内时使用归一化，但是归一化也用于降低值，正则化也是如此。那么两者之间有什么区别？