prakharg24 commited on
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d2a9289
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1 Parent(s): d946758

Update my_pages/rashomon_developer.py

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  1. my_pages/rashomon_developer.py +8 -8
my_pages/rashomon_developer.py CHANGED
@@ -13,14 +13,14 @@ def render():
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  add_instruction_text(
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  """
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  Consider the following data about individuals who did (green) or didn't (red) repay their loans. <br>
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- Make model development choices now that will lead you to the same variety of models as before.
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  """
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  )
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  #### Choosing regularization
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  st.markdown("""
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  **Regularization:** Regularization is a technique that prevents the model from “overfitting,” meaning stop them from learning the noise or small quirks in the data.
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- Regularization helps the model stay more general, so it makes better predictions on new data.<br>
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  Choose a regularization technique:
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  - L1 Regularization: This forces the model to work with as few features as possible, which helps highlight the most important signals and ignore irrelevant ones.
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  - L2 Regularization: This forces the model to rely less on each feature, even though all features are used, which helps prevent any single feature from overpowering the model.
@@ -49,12 +49,12 @@ def render():
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  st.rerun()
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  #### Choosing random seed
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- st.markdown("""
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- **Random Seed:** Random seed controls the stochasticity (or randomness) of the learning process.<br>
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- Choose a random seed.
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- """
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- )
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  if regularization_method=="l1":
 
 
 
 
 
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  random_seed = None
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  if "random_seed" in st.session_state:
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  random_seed = st.session_state.random_seed
@@ -95,6 +95,6 @@ def render():
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  Your choices during model development lead you to this model.
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  """
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  st.markdown(
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- f"<div style='text-align:center; color:#c0392b; font-size:20px; margin:0;'>{multiplicity_message}</div>",
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  unsafe_allow_html=True,
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  )
 
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  add_instruction_text(
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  """
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  Consider the following data about individuals who did (green) or didn't (red) repay their loans. <br>
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+ Make development choices now that will lead to the same variety of models as before.
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  """
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  )
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  #### Choosing regularization
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  st.markdown("""
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  **Regularization:** Regularization is a technique that prevents the model from “overfitting,” meaning stop them from learning the noise or small quirks in the data.
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+
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  Choose a regularization technique:
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  - L1 Regularization: This forces the model to work with as few features as possible, which helps highlight the most important signals and ignore irrelevant ones.
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  - L2 Regularization: This forces the model to rely less on each feature, even though all features are used, which helps prevent any single feature from overpowering the model.
 
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  st.rerun()
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  #### Choosing random seed
 
 
 
 
 
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  if regularization_method=="l1":
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+ st.markdown("""
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+ **Random Seed:** Random seed controls the stochasticity (or randomness) of the learning process.<br>
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+ Choose a random seed.
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+ """
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+ )
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  random_seed = None
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  if "random_seed" in st.session_state:
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  random_seed = st.session_state.random_seed
 
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  Your choices during model development lead you to this model.
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  """
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  st.markdown(
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+ f"<div style='text-align:center; color:#c0392b; font-size:20px;'>{multiplicity_message}</div>",
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  unsafe_allow_html=True,
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  )