如何使用plotly从sklearn创建多元线性回归的散点图？
有X_train和y_train。 X_train下有2个变量。我正在使用多元线性回归来训练模型。如何创建散点图，其中plotly的x有2个变量？
代码看起来像这样：
model = LinearRegression()
model.fit(X, df.tip)
x_range = np.linspace(X.min(), X.max(), 100)
y_range = model.predict(x_range.reshape(-1, 1))
fig = px.scatter(df, x='total_bill', y='tip', opacity=0.65)
fig.add_traces(go.Scatter(x=x_range, y=y_range, name='Regression Fit'))
fig.show()
我遇到了这个错误：
ValueError: matmul: Input operand 1 has a mismatch in its core dimension 0, with
gufunc signature (n?,k),(k,m?)-\>(n?,m?) (size 2 is different from 1)
There are X_train and y_train. There are 2 variables under X_train. I am using multiple linear regression to train the model. How to create a scatter plot where the x for plotly has 2 variables?
The code looks something like this:
model = LinearRegression()
model.fit(X, df.tip)
x_range = np.linspace(X.min(), X.max(), 100)
y_range = model.predict(x_range.reshape(-1, 1))
fig = px.scatter(df, x='total_bill', y='tip', opacity=0.65)
fig.add_traces(go.Scatter(x=x_range, y=y_range, name='Regression Fit'))
fig.show()
I had this error:
ValueError: matmul: Input operand 1 has a mismatch in its core dimension 0, with
gufunc signature (n?,k),(k,m?)-\>(n?,m?) (size 2 is different from 1)
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