CODEWITHSUNDEEP
python-3.xpandasscikit-learnlinear-regression
anInputName
anInputName

Reputation: 449

How to find the standardized residuals with sklearn?

Does sklearn have a method to get the standardized residuals? I have created a dataframe with all the values, the predicted values and the residuals.

Weight  Height  Sex  Age  PredictedWeight  Residual
81.0    177     0    31   81.2             -0.2
78.2    176     0    28   78.8             -0.6
72.5    172     1    29   71.8              0.7
...     ...     ...  ...  ...               ...

The code I have:

from sklearn import linear_model
import pandas as pd

X = df[["Height", "Sex", "Age"]]
Y = df["Weight"]

regr = linear_model.LinearRegression()
regr.fit(X, Y)

df["PredictedWeight"] = regr.predict(df[["Height", "Sex", "Age"]])
df["Residual"] = df["Weight"] - df["Predicted"]

I would like to add a new column to df with the standardized residuals, any suggestions?

Upvotes: 3

Views: 3370

Answers (1)

piterbarg
piterbarg

Reputation: 8219

I think it is simply

mean = df["Residual"].mean()
std = df["Residual"].std()

df["StdResidual"] = (df["Residual"] - mean)/std

or do you want something else?

Upvotes: 5

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