From 5ee4d80eb88f2850c642f0ca140a307317e3da16 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E5=90=B4=E6=9D=A8=E5=B8=86?=
 <39647285+leno23@users.noreply.github.com>
Date: Sun, 17 May 2026 12:10:31 +0800
Subject: [PATCH] docs: fix README typo

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index f0322ca9..aa2e586f 100644
--- a/README.md
+++ b/README.md
@@ -212,7 +212,7 @@ good_function = lambda est, a=a, b=b : new_objective(est=est, a=a, b=b)
 
 ### Tips
 
-TPOT will not check if your data is correctly formatted. It will assume that you have passed in operators that can handle the type of data that was passed in. For instance, if you pass in a pandas dataframe with categorical features and missing data, then you should also include in your configuration operators that can handle those feautures of the data. Alternatively, if you pass in `preprocessing = True`, TPOT will impute missing values, one hot encode categorical features, then standardize the data. (Note that this is currently fitted and transformed on the entire training set before splitting for CV. Later there will be an option to apply per fold, and have the parameters be learnable.)
+TPOT will not check if your data is correctly formatted. It will assume that you have passed in operators that can handle the type of data that was passed in. For instance, if you pass in a pandas dataframe with categorical features and missing data, then you should also include in your configuration operators that can handle those features of the data. Alternatively, if you pass in `preprocessing = True`, TPOT will impute missing values, one hot encode categorical features, then standardize the data. (Note that this is currently fitted and transformed on the entire training set before splitting for CV. Later there will be an option to apply per fold, and have the parameters be learnable.)
 
 
 Setting `verbose` to 5 can be helpful during debugging as it will print out the error generated by failing pipelines.