updated notebook

examples/01_prepare_data/data_prepare_retail.ipynb

@@ -17,7 +17,7 @@
     "\n",
     "This notebook introduces how to split the Orange Juice dataset into training sets and test sets for training and evaluating different retail sales forecasting methods.\n",
     "\n",
-    "We use backtesting a method that tests a predictive model on historical data to evaluate the forecasting methods. Other than standard [K-fold cross validation]( https://en.wikipedia.org/wiki/Cross-validation_\\\\(statistics\\\\) ) which randomly splits data into K folds, we split the data so that any of the time stamps in the training set is no later than any of the time stamps in the test set to ensure that no future information is used (expect certain information that we can know beforehand, e.g., price of the product in the next few weeks as we can set the price manually).\n",
+    "We use backtesting a method that tests a predictive model on historical data to evaluate the forecasting methods. Other than standard [K-fold cross validation](https://en.wikipedia.org/wiki/Cross-validation_\\(statistics\\)#k-fold_cross-validation) which randomly splits data into K folds, we split the data so that any of the time stamps in the training set is no later than any of the time stamps in the test set to ensure that no future information is used (expect certain information that we can know beforehand, e.g., price of the product in the next few weeks as we can set the price manually).\n",
     "\n"
    ]
   },