From 794c0a35aff587052c940987c8f9ec82a0c03f1f Mon Sep 17 00:00:00 2001
From: Jan Ernsting <j.ernsting@uni-muenster.de>
Date: Fri, 25 Nov 2022 11:31:00 +0100
Subject: [PATCH] Updated readme

---
 README.md | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 061422be..a05de5fc 100644
--- a/README.md
+++ b/README.md
@@ -45,8 +45,7 @@ You can setup a full stack machine learning pipeline in a few lines of code:
 from sklearn.datasets import load_breast_cancer
 from sklearn.model_selection import KFold
 
-from photonai.base import Hyperpipe, PipelineElement
-from photonai.optimization import FloatRange, Categorical, IntegerRange
+from photonai import Hyperpipe, PipelineElement, FloatRange, Categorical, IntegerRange
 
 # DESIGN YOUR PIPELINE
 my_pipe = Hyperpipe('basic_svm_pipe',  # the name of your pipeline