ss

pages/3_Training the Model.py

@@ -152,18 +152,22 @@ def step3_page():
             else:
                 st.error("Please upload a valid .csv file")
 
-    st.subheader("Step 2: Data Preprocessing and Feature Engineering")
-    st.write("Now let's preprocess our dataset to handle missing values, outliers and inconsistencies and then perform feature engineering tasks to extract meaningful features from the raw data. Finally we need to separate training variables (X) and target variable (y).")
-    if st.button("Create Features and Target variable"):
-        X, y = create_model_inputs(data, 288, 288)
-        col1, col2 = st.columns([2])
-        with col1:
-            st.subheader("Let's display the Features!")
-            st.dataframe(X)
-        with col2:
-            st.subheader("Let's display our Target variable")
-            st.dataframe(y)
-
+    # st.subheader("Step 2: Data Preprocessing and Feature Engineering")
+    # st.write("Now let's preprocess our dataset to handle missing values, outliers and inconsistencies and then perform feature engineering tasks to extract meaningful features from the raw data. Finally we need to separate training variables (X) and target variable (y).")
+    # if st.button("Create Features and Target variable"):
+    #     X, y = create_model_inputs(data, 288, 288)
+    #     col1, col2 = st.columns([2])
+    #     with col1:
+    #         st.subheader("Let's display the Features!")
+    #         st.dataframe(X)
+    #     with col2:
+    #         st.subheader("Let's display our Target variable")
+    #         st.dataframe(y)
+    #
+    # st.subheader("Step 3: Data Splitting")
+    # st.write(
+    #     "Now let's split into training and testing sets. The training set is used to train the machine learning model, and the testing set is used to evaluate its performance.")
+    # if st.button("Create Features and Target variable"):
         # train_size = st.sidebar.slider("Select Train Dataset Size (%)", min_value=10, max_value=90, value=70)
         #
         # models = ['LightGBM', 'Random Forest']