diff --git a/4-Classification/3-Classifiers-2/README.md b/4-Classification/3-Classifiers-2/README.md index d5d190a33..dd996336c 100644 --- a/4-Classification/3-Classifiers-2/README.md +++ b/4-Classification/3-Classifiers-2/README.md @@ -53,7 +53,7 @@ Following this path, we should start by importing some libraries to use. 1. Split your training and test data: ```python - X_train, X_test, y_train, y_test = train_test_split(cuisines_feature_df, cuisines_label_df, test_size=0.3) + X_train, X_test, y_train, y_test = train_test_split(cuisines_features_df, cuisines_label_df, test_size=0.3) ``` ## Linear SVC classifier diff --git a/4-Classification/3-Classifiers-2/notebook.ipynb b/4-Classification/3-Classifiers-2/notebook.ipynb index 4659a7b62..8f675b0a4 100644 --- a/4-Classification/3-Classifiers-2/notebook.ipynb +++ b/4-Classification/3-Classifiers-2/notebook.ipynb @@ -116,8 +116,8 @@ } ], "source": [ - "cuisines_feature_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n", - "cuisines_feature_df.head()" + "cuisines_features_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n", + "cuisines_features_df.head()" ] } ], diff --git a/4-Classification/3-Classifiers-2/solution/notebook.ipynb b/4-Classification/3-Classifiers-2/solution/notebook.ipynb index a089b21fa..d94f313b9 100644 --- a/4-Classification/3-Classifiers-2/solution/notebook.ipynb +++ b/4-Classification/3-Classifiers-2/solution/notebook.ipynb @@ -116,8 +116,8 @@ } ], "source": [ - "cuisines_feature_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n", - "cuisines_feature_df.head()" + "cuisines_features_df = cuisines_df.drop(['Unnamed: 0', 'cuisine'], axis=1)\n", + "cuisines_features_df.head()" ] }, { @@ -148,7 +148,7 @@ "metadata": {}, "outputs": [], "source": [ - "X_train, X_test, y_train, y_test = train_test_split(cuisines_feature_df, cuisines_label_df, test_size=0.3)" + "X_train, X_test, y_train, y_test = train_test_split(cuisines_features_df, cuisines_label_df, test_size=0.3)" ] }, {