Upload 7 files

app.py

@@ -0,0 +1,102 @@
+import streamlit as st
+import pickle
+import json
+import pandas as pd
+import numpy as np
+
+with open("list_num_skew_columns.txt", 'r') as file_1:
+    list_num_skew_columns = json.load(file_1)
+
+with open("list_cat_nom_columns.txt", "r") as file_2:
+    num_col_skew = json.load(file_2)
+
+with open("scaler_minmax.pkl", "rb") as file_3:
+    model_scaler = pickle.load(file_3)
+
+with open("encoder_n.pkl", "rb") as file_4:
+    model_nominal_encoder = pickle.load(file_4)
+
+with open("knn_gridcv_best.pkl", "rb") as file_5:
+    knn_gridcv_best = pickle.load(file_5)
+
+def run():
+    # create form 
+    with st.form("form_payment"):
+        age = st.number_input("age",
+                            min_value= 20,
+                            max_value= 70,
+                            value=30,
+                            step=2) 
+        
+        limit_balance = st.slider("limit_balance",0,800000)
+        bill_amt_1 = st.slider("bill_amt_1",-100000,600000)
+        bill_amt_2 = st.slider("bill_amt_2",-100000,600000)
+        bill_amt_3 = st.slider("bill_amt_3",-100000,600000)
+        bill_amt_4 = st.slider("bill_amt_4",-100000,600000)
+        bill_amt_5 = st.slider("bill_amt_5",-100000,600000)
+        bill_amt_6 = st.slider("bill_amt_6",-100000,600000)
+        st.markdown("---")
+        pay_amt_1 = st.slider("pay_amt_1",-0,1000000)
+        pay_amt_2 = st.slider("pay_amt_2",-0,1000000)
+        pay_amt_3 = st.slider("pay_amt_3",-0,1000000)
+        pay_amt_4 = st.slider("pay_amt_4",-0,1000000)
+        pay_amt_5 = st.slider("pay_amt_5",-0,1000000)
+        pay_amt_6 = st.slider("pay_amt_6",-0,1000000)
+
+        st.markdown("---")
+        sex = st.radio("sex",("1","2"),help="1 for male,2 for female",index= 0)
+        education_level = st.radio("education level",("0","1","2","3","4","5","6"),index= 0)
+        marital_status = st.radio("marital_status",("0","1","2","3"),index= 0)
+        
+        st.markdown("---")
+        pay_0 = st.radio("pay_0",("-2","-1","0","1","2","3","4","5","6","7","8"),index= 0)
+        pay_2 = st.radio("pay_2",("-2","-1","0","1","2","3","4","5","6","7","8"),index= 0)
+        pay_3 = st.radio("pay_3",("-2","-1","0","1","2","3","4","5","6","7","8"),index= 0)
+        pay_4 = st.radio("pay_4",("-2","-1","0","1","2","3","4","5","6","7","8"),index= 0)
+        pay_5 = st.radio("pay_5",("-2","-1","0","1","2","3","4","5","6","7","8"),index= 0)
+        pay_6 = st.radio("pay_6",("-2","-1","0","1","2","3","4","5","6","7","8"),index= 0)
+        st.markdown("---")
+
+        submitted = st.form_submit_button("predict")
+
+    data_inf = {
+        "limit_balance" : limit_balance,
+        "sex" : sex,
+        "education_level" : education_level,
+        "marital_status" : marital_status,
+        "age" : age,
+        "pay_0" : pay_0, 
+        "pay_2" : pay_2, 
+        "pay_3" : pay_3, 
+        "pay_4" : pay_4, 
+        "pay_5" : pay_5, 
+        "pay_6" : pay_6,
+        "bill_amt_1" : bill_amt_1, 
+        "bill_amt_2" : bill_amt_2,
+        "bill_amt_3" : bill_amt_3, 
+        "bill_amt_4" : bill_amt_4, 
+        "bill_amt_5" : bill_amt_5, 
+        "bill_amt_6" : bill_amt_6, 
+        "pay_amt_1" : pay_amt_1, 
+        "pay_amt_2" : pay_amt_2,
+        "pay_amt_3" : pay_amt_3, 
+        "pay_amt_4" : pay_amt_4, 
+        "pay_amt_5" : pay_amt_5, 
+        "pay_amt_6" : pay_amt_6       
+    }
+
+    data_inf = pd.DataFrame([data_inf])
+    st.dataframe(data_inf)
+
+    if submitted:
+        data_inf_num_skew = data_inf[list_num_skew_columns]
+        data_inf_cat_nom = data_inf[num_col_skew]
+        data_inf_num_scal = model_scaler.transform(data_inf_num_skew)
+        data_inf_cat_nom_enc = model_nominal_encoder.transform(data_inf_cat_nom)
+        data_inf_final = np.concatenate([data_inf_num_scal,data_inf_cat_nom_enc],axis=1)
+        y_predict_inf = knn_gridcv_best.predict(data_inf_final)
+
+        st.write("# Default_payment: ",str(int(y_inf_pred)))
+
+if __name__=="__main__":
+    run()

encoder_n.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd3a1dd87d75d1e40721edeb9e18c71d274666715e72f41a084d604eb70adf3b
+size 1281

knn_gridcv_best.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07180f84b3c0f168bab0d5ec66fa59629515fadd3157971b45326931728458ee
+size 1233587

list_cat_nom_columns.txt

@@ -0,0 +1 @@
+["pay_0", "pay_2", "pay_3", "pay_4", "pay_5", "pay_6"]

list_num_skew_columns.txt

@@ -0,0 +1 @@
+["limit_balance", "pay_amt_1", "pay_amt_2", "pay_amt_3", "pay_amt_4", "pay_amt_5", "pay_amt_6"]

requirements.txt

@@ -0,0 +1,6 @@
+streamlit
+pandas
+numpy
+matplotlib
+seaborn
+scikit-learn

scaler_minmax.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0897120071f4f620b633a3a8b8e7f55ef8caec6dd963fbb5f1381585df73de04
+size 936